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List of PDF Full Texts available from EurekaMag Chapter 35535

Chapter 35535 contains a list of PDF Full Texts available from EurekaMag.





Reimer, C.T., 1999:
Predator-induced morphological variation in predatory snails, Nucella spp Tests using field experiments

Brodie, E.D.IIi; Brodie, E.D.Jr, 1999:
Predator-prey arms races Asymmetrical selection on predators and prey may be reduced when prey are dangerous

Wood, A.D.; Wetherbee, B.; Kohler, N.; Juanes, F.; Wilga, C., 2003:
Predator-prey interaction between the shortfin mako, Isurus oxyrinchus, and bluefish, Pomatomus saltatrix

Hristov, N.I.; Conner, W.E., 2002:
Predator-prey interactions A new analysis of the bat-moth arms race

Morton, Brian, 2004:
Predator-prey interactions between Lepsiella vinosa and Xenostrobus inconstans in a southwest Australian marsh

Turingan, R.G.; Beck, J.L., 2001:
Predator-prey interactions in the marine plankton Functional and morphological bases of prey-capture performance in marine fish larvae

Price, N.N.; Mensinger, A.F., 1999:
Predator-prey interactions of first year toadfish Opsanus tau

Manderson, J.P.; Phelan, B.A.; Stoner, A.W.; Hilbert, J., 2000:
Predator-prey relations between age-1 + summer flounder and age-0 winter flounder Predator diets, prey selection, and effects of sediments and macrophytes

Minami, Takashi, 2000:
Predator-prey relationship and trophic levels of the pink shrimp, Pandalus eous, in the Yamato Bank, the Sea of Japan

Vacchi, M.; Cattaneo Vietti, R.; Chiantore, M.; Dalu, M., 2000:
Predator-prey relationship between the nototheniid fish Trematomus bernacchii and the Antarctic scallop Adamussium colbecki at Terra Nova Bay

Hall, S.R.; Leibold, M.A.; Lytle, D.A.; Smith, V.H., 2001:
Predators and stoichiometric traits of phytoplankton autotrophs and zooplankton grazers influence community- and ecosystem-level patterns

Relyea, Rick, A., 2001:
Predators come and predators go The reversibility of phenotypic plasticity in tadpoles

Ferla, N.J.arez; D.M.raes, G.J.se, 2002:
Predators mites in native and cultivated plants of the state of Rio Grande do Sul, Brazil

Panis, Andre, 1999:
Predators of the Mediterranean black scale, Saissetia oleae , from France

Pires, C.V.; Meissner, K., 2001:
Predators without locomotion Pit construction, feeding and survival of antlions

Blackledge, Todd, A., 2001:
Predators, prey, and the decoration of spider webs with stabilimenta

Menn, I.; Armonies, W., 1999:
Predatory Promesostoma species in the Wadden Sea

Kondo, A.; Hiramatsu, T., 1999:
Predatory ability of two species of phytoseiid mites on the peach silver mite, Aculus fockeui

Mesquita, A.L.M.; Lacey, L.A.; Ceianu, C.S.; Dabire, R., 1999:
Predatory and parasitic activity of Aphelinus asychis following exposure to the entomopathogenic fungus Paecilomyces fumosoroseus under different humidity regimes

Markelova, N.Y., 2003:
Predatory bacteria, Bdellovibrio Survival strategy and potential for use

Hoelldobler, B.; Oldham, N.J.; Alpert, G.D.; Liebig, J., 2002:
Predatory behavior and chemical communication in two Metapone species

Takano Lee, M.; Hoddle, M., 2002:
Predatory behaviors of Neoseiulus californicus and Galendromus helveolus attacking Oligonychus perseae

Matthews, Martin, 2003:
Predatory behaviour of Carabus glabratus Paykull in the Cairngorms

Bon, Mauro, 1999:
Predatory behaviour of Larus cachinnans against Columba livia in Venice

Deligeorgidis, P.N., 2002:
Predatory effect of Orius niger on Frankliniella occidentalis and Thrips tabaci Lindeman

Haque, M.M.inul; Kawai, A., 2003:
Predatory efficiency of Homeopronematus anconai on Aculops lycopersici

Blackledge, T.A.; Pickett, K.M., 2000:
Predatory interactions between mud-dauber wasps and Argiope in captivity

Grout, T.G.; Ueckermann, E.A., 1999:
Predatory mites found under citrus trees in the Southern African lowveld

Japyassu, H.F.rreira; Viera, C., 2001:
Predatory plasticity in Nephilengys cruentata Relevance for phylogeny reconstruction

Babu, A., 2001:
Predatory potential and life parameters of Cheilomenus sexmaculata in relation to energetics of Aphis gossypii glover

Signore, Marco, 2001:
Predatory strike in some maniraptoran dinosaurs

Weiss, M.R.; Wilson, E.E.; Castellanos, I., 2002:
Predatory wasps learn to overcome the shelter defenses of their larval prey

Austin, J.; Sell, A.; Horgan, E.; Madin, L., 1999:
Predatory, planktonic hydroids on Georges Bank Behavioral response to naupliar copepod prey

D.Z.egler, D.; Hoffman, P.; Pons, J.C.; Quenard, N.; Ayoubi, J.M., 2001:
Predetermining the day of ovulation in the menstrual cycle by controlling the inter-cycle FSH rise with exogenous oestradiol Application for timing post coital tests

Blasetti, A.; Verrotti, A.; Tumini, S.; Borgia, M.; Chiarelli, F., 1999:
Prediabetes: an unusual case

Vendrame, F.; Gottlieb, P.A., 2004:
Prediabetes: prediction and prevention trials

Macfarlane, A.J.; Scott, F.W., 2004:
Prediabetic NOD Mice have Increased Antibodies to Glb1, a Wheat Storage Globulin

Brooks, J.D.; Metter, E.J.ffrey; Chan, D.W.; Sokoll, L.J.; Landis, P.; Nelson, W.G.; Muller, D.; Andres, R.; Carter, H.B.llentine, 1999 :
Prediagnostic serum selenium levels and the risk of prostate cancer development

Platz, E.A.; Helzlsouer, K.J.; Hoffman, S.C.; Morris, J.Steven.; Baskett, C.K.; Comstock, G.W., 2002:
Prediagnostic toenail cadmium and zinc and subsequent prostate cancer risk

Wong, T.Y.H.; Li, P.K.T., 2003:
Predialysis care in diabetic patients: the missing link?

Hibberd, A.D.; Trevillian, P.R.; Wlodarzcyk, J.H.; Gillies, A.H.; Stein, A.M.; Sheil, A.G.; Disney, A.P., 2001:
Predialysis immunosuppression is an independent risk factor for some cancers in renal transplantation

Lorenzo, V.; Rufino, M.; Martin, B.; Jimenez, A.; Hernandez, D.; Torres, A., 2002:
Predialysis nephrological care and a functioning vascular access at entry improves survival of patients starting maintenance hemodialysis

Wong, C.; Lele, S., 1999:
Predicative value of CA125 to second-look surgery

Pfautsch, P.; Frantz, E.; Baumann, M.; Hammann, J.; Fleck, E., 2000:
Predicitors of mortality and re-intervention in patients treated by angioplasty for recurrent angina after coronary artery bypass grafting

Nicolcescu, P.; Purcaru, F.; Georgescu, I.; Silvia, V.; Emilia, P., 2001:
Predict the difficult laryngoscopy in general surgery department, plastic and reconstructive surgery department, neurosurgery department, otorinolaryngology department and obstetric department

Loo, R.H.; Thompson, J.T.; Sjaarda, R.N., 1999:
Predictability of bilateral macular hole surgery

Rachelefsky, G.S.; Salmun, L.M.; Banfield, C., 2001:
Predictability of desloratadine Lack of clinical interaction with food and concomitant medications

Zwiers, S.H.; Shamblin, J.D.; Baker, R.O.; Huggins, J.W., 2003:
Predictability of genome levels in blood for levels in tissues of cowpox infected mice

Matson, S.E.; Langdon, C.; Evans, F.; Brake, J.; Jacobson, D., 2002:
Predictability of grow-out performance from nursery performance of Pacific oyster, Crassostrea gigas

Ripley, L.S., 1999:
Predictability of mutant sequences. Relationships between mutational mechanisms and mutant specificity

Santiago, M.C.; Miller, T.L.; Schrader, G.R., 1999:
Predictability of peak heart rate when distance from the crank axis is controlled during arm crank ergometry with adult women

Sylvester, S.; Mathew, M.; Abraham, G.; Cherian, K.M., 2001:
Predictability of post operative acute renal failure in patients undergoing cardiovascular surgery

Chen, R.; Gimbel, H.V.; Penno, E.A.derson; Cuzzani, O.E.; Feinerman, G., 1999:
Predictability of refractive surgery outcome between artificial neural network intelligence and refractive surgeons

Moreno Monteagudo, J.A.dres; Trapero Marugan, M.; Garcia Buey, L.; Borque, M.J.sus; Moreno Otero, R., 2002:
Predictability of response to interferon plus ribavirin in chronic hepatitis C patients

Adkison, M.D.; Peterman, R.M., 1999:
Predictability of returns of sockeye salmon to Bristol Bay, Alaska, 1-4 years in the future

Carney, P.R.; Iasemidis, L.D.; Pardalos, P.; Srivastava, A.; Won, J.; Shiau, D.S.; Lee, N.; Maclennan, A.J.hn; Sackellares, J.C.ris, 2001:
Predictability of seizures in an epilepsy-prone transgenic mouse model

Reeve, V.E., 1999:
Predictability of sunscreen protection from photocarcinogenesis by protection from photoimmunosuppression

Klais, C.M.; Hattenbach, L.O.; Vanselow, K.; Kohnen, T.; Zubcov, A., 2000:
Predictability of the early post-operative refractive status after pediatric cataract surgery and IOL implantation using the Holladay II formula

Cook, J.; Zheng, A.; Hurst, S.; Lalonde, R., 2001:
Predictability of the magnitude of CYP3A4 mediated drug interactions from in vitro Ki values

Mazzaferro, S.; Ronci, R.; Pasquali, M.; Angeloni, V.; Onorato, L.; D.M.rtino, A.; Rubino, F.; Aleandri, M.; Fioravanti, P.M.; Cinotti, G.A., 1999:
Predictability of therapeutic response to calcitriol in dialysis patients

Beran, R.G.; Hung, A.; Plunkett, M.; Currie, J.; Sachinwalla, T., 1999:
Predictability of visual field defects in patients exposed to GABAergic agents, vigabatrin, or tiagabine

Meiners, S.J.; Cadenasso, M.L.; Pickett, S.T., 2003:
Predictability of within-site invasion dynamics for native and exotic plant species

Ayala, D.E.; Hermida, R.C.; Mojon, A.; Fernandez, J.R.; Alonso, I., 2001:
Predictable blood pressure changes along gestation in healthy and complicated pregnancies

Ayala, D.E.; Hermida, R.C.; Fernandez, J.R.; Iglesias, M., 2001:
Predictable blood pressure variability along gestation in healthy and complicated pregnancies

Williams, T.C.; Rahn, P., 2001:
Predictable carbon de-colorization process for small scale

Ayala, D.E.; Hermida, R.C.; Fernandez, J.R.; Mojon, A.; Alonso, I.; Aguilar, M.F.; Codesido, J.; Iglesias, M., 2003:
Predictable changes in double product along gestation in normotensive and hypertensive pregnant women

Nap, J.P.ter; Mlynarova, L'udmila; Loonen, A.; Mietkiewska, E.; Hutvagner, G.; Bekesiova, I.; Moravcikova, J.; Matusova, R.; Stiekema, W.J., 1999:
Predictable expression of transgenes in plants The chromatin connection

Meilander, W.; Baker, J., 2001:
Predictable real-time scheduling for air traffic control

Stange, J.; Broelsch, C.; Gerken, G.; Treichel, U.; Heemann, U.; Liebe, S.; Hassanein, T.I., 2001:
Predictably Ltx-costs of progressive cholestasis in end stage liver disease can be reduced by albumin dialysis Results of a prospective controlled randomized trial

Sumino, Y.; Yoshihisa, H.; Ohna, H.; Hoshino, T.; Nomura, T.; Nomura, Y., 2001:
Predictators of lower pole stone clearance after extracorporeal shock wave lithotripsy

Guerra, M.; Dasilva, A.; Pitetti, K.H.; Fernhall, B., 2002:
Predicted aerobic capacity in children and adolescents with Down Syndrome

Springer, T.A., 2002:
Predicted and experimental structures of integrins and beta-propellers

Rezende,K.F.; Ferraz,M.B.; Malerbi,D.A.; Melo,N.H.; Nunes,M.P.; Pedrosa,H.C.; Chacra,A.R., 2010:
Predicted annual costs for inpatients with diabetes and foot ulcers in a developing country - a simulation of the current situation in Brazil

Coles, L.T.; Moughan, P.J.; Awati, A.; Darragh, A.J.; Zou, M.L., 2010:
Predicted apparent digestion of energy-yielding nutrients differs between the upper and lower digestive tracts in rats and humans

Paul, K.I.; Polglase, P.J.; Richards, G.P., 2003:
Predicted change in soil carbon following afforestation or reforestation, and analysis of controlling factors by linking a C accounting model to models of forest growth , litter decomposition and soil C turnover

Coval, S.M.; Zhao, G.; Huth, P.; Kris Etherton, P.M., 2000:
Predicted changes in TC, LDL-C, HDL-C, and TG in response to changes in dietary n-3 and n-6 fatty acids

Zasadny, K.R.; Longino, M.A.; Fisher, S.J.; Counsell, R.E.; Wahl, R.L., 1999:
Predicted dosimetry for I-131-NM-404, a phospholipid ether agent for tumor imaging and possible therapy

Krasowski, G.W.; Kruk, M.; Geremek, M.; Trochimczuk, M.; Borkowski, M., 2001:
Predicted efficacy of antibiotic therapy in surgical infections based on monitoring bacterial culture and its resistance

Jackson, S.H., 1999:
Predicted exposure concentrations in the Po River Valley using the RICEWQ model

Svojanovsky, S.R.; Hobson, G.M.; Sperle, K.; Sistermans, E.A.; Garbern, J.Y.; Rogan, P.K., 2001:
Predicted expression of PLP1 splicing mutations in Pelizaeus-Merzbacher disease

Kim, C.S.; Gumbs, A.A.; Komarnicky, L.; Carter, D.; Hutter, R.; Palazzo, J.P.; Mccue, P.A.; Goodman, R.; Haffty, B.G.; Rebbeck, T.R.; Weber, B.L.; Turner, B.C., 2000:
Predicted germline BRCA1/BRCA2 mutations and second primary ipsilateral breast cancers in young women with pure ductal carcinoma in-situ treated with breast conserving therapy

Rebelo,H.; Tarroso,P.; Jones,G., 2010:
Predicted impact of climate change on European bats in relation to their biogeographic patterns

Yeo, W.W.; Yeo, K.R.wland, 2001:
Predicted impact of the National Service Framework for coronary heart disease on statin prescribing

Barton, H.; Zachwieja, Z.; Folta, M., 2002:
Predicted intake of trace elements and minerals via household drinking water by 6-year-old children from Krakow Part 1 Lead

Barton, H., 2010:
Predicted intake of trace elements and minerals via household drinking water by 6-year-old children from Krakow, Poland. Part 5: Zinc

Mcmurray, R.G.; Harrell, J.S.; Bradley, C.; Deng, S.; Bangdiwala, S.I., 2001:
Predicted maximal aerobic power in youth is related to gender, ethnicity, and body composition The CHIC Study

Gibbons, I.R.; Mocz, G., 2000:
Predicted model for the motor component of dynein heavy chain based on homology to the AAA family of oligomeric ATPases

Blackwood, A.; Yang, H.; Nathason, K.; Stratton, M.; Easton, D.; Calzone, K.; Stopfer, J.; Olopade, O.; Cummings, S.; Ganguly, A.; Berlin, J.; Weber, B., 2001:
Predicted probability of breast cancer susceptibility gene mutations

Tseveenjav, B.; Norman, M.; Golden, B.L.; Blackburn, H.D., 2002:
Predicted rate of inbreeding for a closed line of Hereford cattle

Rosemurgy, A.S.; Bloomsotn, M.; Blank, S.; Serafini, F., 2001:
Predicted vs actual survival following TIPS vs H-graft portacaval shunt

Wilson, G.S.; Steinke, J.A.; Raglin, J.S., 2000:
Predicted, precompetition, and competition anxiety in optimistic and pessimistic collegiate softball players

Werner, G.C.; Twomey, J.; Solem, L.D., 1999:
Predictibility of medical costs incurred in the industrial arena

Giri, K.S.; Freeman, R.; Mehta, R.H.; Rosenthal, J.; Leichtman, A.; Armstrong, W., 2002:
Predicting 30-day cardiovascular outcomes in diabetic renal transplant recipients using dobutamine echo

Sayers, S.P.; Brach, J.; Newman, A.; Guralnik, J.; Fielding, R.A., 2003:
Predicting 400 meter walk performance from questionnaire

Shipley, R.; Green, J.S.; Crouse, S.F., 2001:
Predicting 48-hour post exercise HDL-cholesterol changes in hyperlipidemic men

Miranda, V.; Reyna, V.F.; Lloyd, F.J.; Whalen, P.K.; Pottahil, V.; Hazel, A., 2002:
Predicting Acute Cardiac Ischemia Judgments, guidelines, and outcomes

Korn, M.; Gärtner, T.; Erban, A.; Kopka, J.; Selbig, J.; Hincha, D.K., 2010:
Predicting Arabidopsis freezing tolerance and heterosis in freezing tolerance from metabolite composition

Iyo, C.; Kawano, S., 2003:
Predicting Brix values of stored apples using near infrared spectra

Lewis, K.; Watkins, A.; Bartle, I.; Hutchings, H.; Ebden, P., 2000:
Predicting CPAP machine use in treating obstructive sleep apnoea

Pareek, G.; Bruno, J.J.mes; Panagopoulos, G.; Armenakas, N.A.; Fracchia, J.A., 2004:
Predicting ESWL stone-free rates using body mass index and hounsfield units

Richards, S.A.; Patterson, K.L.; Pascual, M.; Porter, J.W., 2003:
Predicting Elkhorn Coral dynamics throughout the Florida Keys

Preisman, S.; Kogan, S.; Berkenstadt, H.; Perel, A., 2003 :
Predicting Fluid Responsiveness in Cardiac Surgical Patients Functional Hemodynamic Parameters Versus Cardiac Preload Indicators

Solus Biguenet, H.; Fleyfel, M.; Lebuffe, G.; Tavernier, B.; Vallet, B., 2003:
Predicting Fluid Responsiveness in Major Hepatic Surgery Dynamic Versus Static Hemodynamic Parameters

Schaafsma, A.W.; Tamburic Ilincic, L.; Hooker, D.; Duke, C., 1999:
Predicting Fusarium head blight and deoxynivalenol in winter wheat using near real time weather data

Copeland, S.; Mchugh, J.; Welch, K.; Siddiqui, J.; Remick, D., 2004:
Predicting Gram-Positive or Gram-Negative Bacteraemia with Plasma Cytokine Levels

Neumann, A.U.; Havlin, Y.; Ronen, T.; Tsiang, M.; Wulfsohn, M.; Brosgart, C.; Fry, J.; Westland, C.; Xiong, S.; Gibbs, C.S., 2003:
Predicting HBeAg loss by HBV DNA early kinetics and HBV genotype during treatment of HBeAg+ chronic hepatitis B patients with adefovir dipivoxil

Bilous, M., 2002:
Predicting HER2 status of breast cancer from basic pathology features HER2 status of 1500 breast cancers determined by immunohistochemistry and fluorescence in situ hybridisation with pathology correlation

Jensen, M.A.; van 't Wout, Aélique.B., 2003:
Predicting HIV-1 coreceptor usage with sequence analysis

Capparelli, A.W.; Wilson, S., 1999:
Predicting Hepatitis B vaccination failure in ESRD

Youn,H.W.; Gu,Z., 2010:
Predicting Korean lodging firm failures an artificial neural network model along with a logistic regression model

Niksa, S.; Liu, G.; Felix, L.; Bush, P.V.nn; Boylan, D.M., 2003:
Predicting NOX emissions from biomass cofiring

Sano, M.C.; Berg, J.D.; Knopman, D.; Farlow, M.R.; Thomas, R.G., 2000:
Predicting Nursing Home Placement with change on cognitive measures in Alzheimers Disease

Collett, A.; Tanianis-Hughes, J.; Hallifax, D.; Warhurst, G., 2004:
Predicting P-glycoprotein effects on oral absorption: correlation of transport in Caco-2 with drug pharmacokinetics in wild-type and mdr1a(-/-) mice in vivo

Visaria, R.; Westenskow, D.R., 2003:
Predicting Pulmonary Mechanics Noninvasively in Real Time during Surgery

Yu, X.; Zhou, S.; Kahn, D.; Ahn, S.; Shafman, T.; Hollis, D.; Light, K.; Tisch, A.; Folz, R.; Jaszczak, R.; Coleman, R.; Marks, L.B., 2003:
Predicting RT-induced pulmonary symptoms based on the dose to the superior vs inferior lung in patients irradiated for lung cancer

Henry, D.; Niederef, K.; Nazarian, D.; Keck, G.; Pavia, A.M.rie, 2002:
Predicting Response to Preoperative Subcutaneous Erythropoietin and Intravenous Iron

Bohen, S.P.; Troyanskaya, O.; Alter, O.; Warnke, R.; Botstein, D.; Brown, P.O.; Levy, R., 2002:
Predicting Rituximab Response of Follicular Lymphoma Using cDNA Microarray Analysis

Shah, N.P.; Nicoll, J.M.; Graeber, T.; Paquette, R.L.; Sawyers, C.L., 2002:
Predicting Survival and Response in Myeloid Blast Crisis CML Patients Using Microarray Analysis Prior to Administration of the Tyrosine Kinase Inhibitor Imatinib

Pitetti, K.H.; Fernhall, B.; Figoni, S.F., 2000:
Predicting VO2PEAK using the 20-M shuttle run for children and adolescents A comparison

Wood, R.H.; Ermolao, A.; Ferachi, K.; Fuller, S., 2003:
Predicting VO2max of older adults from oxygen uptake efficiency during the CS-PFP functional fitness test

Seeney, F.M..; Mahler, J.; Sharples, L.; Parameshwar, J., 2001:
Predicting a patient's waiting time to heart transplant in the UK

Kanaya, A.; Fyr, C.W.ssel; D.R.keniere, N.; Shorr, R.; Schwartz, A.; Rubin, S.; Barrett Connor, E., 2003:
Predicting abnormal glucose tolerance in older adults The derivation and validation of a prediction rule

Owens, D.A.fred; Andre, J.T.; Owens, R.L., 2000:
Predicting accommodative performance in difficult conditions A behavioral analysis of normal variations of accommodation

Schaben, J.A.; Welk, G.J., 2002:
Predicting activity patterns when children have the same opportunity to be active

Flury, L.; Foroud, T.; Ramchandani, V.A.; Morzorati, S.; Kareken, D.; Blekher, T.; Li, T.K.; O'connor, S., 2001:
Predicting acute tolerance adaptation to alcohol

Epstein, R.; Herer, P.; Tzischinsky, O.; Lavie, P., 2002:
Predicting adaptation to shift work A validation of a new method

Rawl, S.M.; Blackburn, S.; Hackward, L.; Fineberg, N.S.; Imperiale, T.; Rahmani, E.; Rex, D., 2001:
Predicting adherence to colorectal cancer surveillance after polypectomy

Okah, F.A.; Okuyemi, K.S.; Harris, K.J.; Mccarter, K.S.; Catley, D.; Ahluwalia, J.S., 2002:
Predicting adoption of home smoking restrictions by inner-city African American smokers

Milroy, C.J.; Wilson, G.; Sanders, R., 1999:
Predicting adverse outcome in basal cell carcinoma

Wolf, A.L.; Pettinati, H.M.; Luck, G.J.; Volpicelli, J.R., 1999:
Predicting alcohol consumption The interaction of abuse and gender in a naltrexone trial

Thomas, S.E.; Drobes, D.J.; Deas, D., 2002:
Predicting alcohol cue reactivity in adolescent alcoholics

Walton, M.A.; Blow, F.C.; Maio, R.; Barry, K.; Bingham, C.R., 2002:
Predicting alcohol misuse among injured patients in the emergency department

Duska Mcewen, G.; Courtad, K.L.; Johns, P.W.; Malone, W.T.; Borschel, M.W.; Cordle, C.T., 1999:
Predicting allergenic reactivity of elemental nutritionals

Jaikaran, S.; Prommer, E.; Salmon, D.; Hsu, H.; Recinos Diaz, G., 2002:
Predicting amino acids in triticale by NIRS and simple regression equations

Jaikaran, S.; Prommer, E.; Mckenzie, R.; Hsu, H.; Recinos Diaz, G., 2001:
Predicting amino acids in wheat by NIRS and simple regression equations

Cunha, M.R.; Moreira, M.H.; Sorbe, J.C., 2000:
Predicting amphipods brood size variation in brackish environments An empirical model for Corophium multisetosum stock, 1952 in Ria de Aveiro

Debold, Adolfo, J., 2000:
Predicting and detecting cardiac allograft rejection

Roberts, S.N.C.mpbell; Williams, A.C.; Grimsey, I.M.; Booth, S., 2000:
Predicting and evaluating the relative stability of mannitol polymorphs from single physico-chemical measurements

Rodgers, E.C.; Flynn, K.A.; Mcvey, K.M., 2002 :
Predicting and preventing injuries by considering seizure classification

Macgregor, E.A.ne; Frith, A.; Ellis, J.; Aspinall, L., 2003:
Predicting and preventing menstrual migraine Use of the Clearplan Fertility Monitor

Cannon, Christopher, P., 2002:
Predicting and preventing myocardial infarction with clopidogrel in patients with symptomatic atherothrombosis Results from CAPRIE

Melis,C.; Herfindal,I.; Kauhala,K.; Andersen,R.; Hogda,K.A., 2010:
Predicting animal performance through climatic and plant phenology variables the case of an omnivore hibernating species in Finland

Patel, R.; Saylor, T.; Schneir, A.; Clark, R.F., 2002:
Predicting antimuscarinic agent poisoning based on clinical signs and symptoms

Nordin, K.; Berglund, G.; Glimelius, B.; Sjoden, P.O., 1999:
Predicting anxiety and depression among cancer patients

Mobley, C.N.; Celano, M.; Phillips, K.; Linzer, J., 2004:
Predicting asthma symptoms in low-income children with persistent asthma The role of medication adherence, depressive symptoms and behavior problems

Mcdonald, R.A.; Klopfenstein, T.J.; Erickson, G.E.; Loy, T.W., 2003:
Predicting bacterial crude protein production from urinary allantoin in spot samples

Conroy, S.B.; Drennan, M.J.; McGee, M.; Keane, M.G.; Kenny, D.A.; Berry, D.P., 2010:
Predicting beef carcass meat, fat and bone proportions from carcass conformation and fat scores or hindquarter dissection

Gohlke, H.; Hendlich, M.; Klebe, G., 2000:
Predicting binding modes, binding affinities and hot spots for protein-ligand complexes using a knowledge-based scoring function

Jortani, S.A.; Falamarzian, M.; Varshosaz, J.; Ghafghazi, T.; Raisi, A., 1999:
Predicting bioavailability of different tablet formulations of aminophylline and theophylline by assessing their dissolution rates

Glazier, D.B.; Marmar, J.L.; Krish, E.B.; Chen, Y.; Ejudi, S.; Koprowski, C.D., 1999:
Predicting biochemical failures from baseline prostate specific antigen, prostate specific antigen density and Gleason score in patients treated with brachytherapy for prostate carcinoma

Geyer, H.J.; Kaune, A.; Schramm, K.W.rner; Rimkus, G.; Scheunert, I.; Brueggemann, R.; Altschuh, J.; Steinberg, C.E.; Vetter, W.; Kettrup, A.; Muir, D.C.G., 1999:
Predicting bioconcentration factors of polychlorinated bornane congeners in fish and comparison with bioaccumulation factors in biota from the aquatic environment

Knaebel, D.B.; Howard, P.H.; Gray, D.A., 2002:
Predicting biodegradation in soils-statistical analysis, model generation, and software development

Ellis, L.B.M.; Hershberger, C.D.; Wackett, L.P., 1999:
Predicting biodegradation pathways

Nam, K.; Honer, C.; Schumacher, C.; Berry, C.; Marshall, P.; Cornell, W., 2002:
Predicting biological activity of a set of compounds using machine learning algorithms

Federman, A.D.; Wisnivesky, J.P.; Trost, D.; Bloch, M.J.; Henschke, C.I.; Rottgardt, F.; Paccione, G.; Mcginn, T.G., 1999:
Predicting blood pressure response in patients undergoing renal artery angioplasty

Makinen, H.; Ojansuu, R.; Sairanen, P.; Yli Kojola, H., 2003:
Predicting branch characteristics of Norway spruce Karst from simple stand and tree measurements

Van, D.Vijver, M., 2003:
Predicting breast cancer behaviour by genetic analysis

Ralph, D.; Aston, C.; Thompson, L.; West, A.; Branam, D.; Lee, A.; Craft, M.; Mitchell, D.; Jupe, E., 2002:
Predicting breast cancer risk with combinations of genetic polymorphisms

Taylor, L.J.; Papadopoulos, D.G.; Dunn, P.J.; Mitchell, J.C.; Snowden, M.J., 2003:
Predicting bulk powder behaviour from single crystals

Tozer, P.R.; Scollard, D.L.; Marsh, T.L.; Marsh, T.J., 1999:
Predicting calving ease peri-partum

Kronz, J.D.; Allan, C.H.; Shaikh, A.A.; Epstein, J.I., 2001:
Predicting cancer following a diagnosis of high grade PIN on needle biopsy

Cheli, C.D.; Bartsch, G.; Babaian, R.; Fritsche, H.; Sokoll, L.; Chan, D.; Partin, A.; Taneja, S.; Brawer, M., 2002:
Predicting cancer on repeat biopsy Results of a multicenter prospective evaluation of Complexed PSA

Brawer, M.K.; Ferreri, L.F.; Kim, B.; Asfaw, T., 2000:
Predicting cancer on repeat prostate needle biopsy The utility of alpha 1-antichymotrypsin complex prostate specific antigen /PSA ratio

Rieger, K.R.; Tusher, V.G.; Hong, W.; Tang, J.; Tibshirani, R.; Chu, G., 2002:
Predicting cancer risk and treatment toxicity by microarray analysis of transcriptional responses to DNA damage

Belinsky, Steven, 2003:
Predicting cancer risk and tumor progression through detection of gene promoter hypermethylation in sputum and plasma

Sparano, J.A.; Brown, D.L.; Wolff, A.C., 2002:
Predicting cancer therapy-induced cardiotoxicity: the role of troponins and other markers

Louis, J.C., 2003:
Predicting carcinogenicity early The latest in silico solution

Prieto, L.M.rina; Solano, M.; Mintz, D.; Skyler, J.; Meneghini, L., 2003:
Predicting cardiac autonomic dysfunction in a specialized academic diabetes center

Hausberg, M.; Barenbrock, M., 2002:
Predicting cardiovascular risk in populations

Tylutki, T.P.; Fox, D.G.; Chase, L.E., 2002:
Predicting cattle phosphorus excretion

Qureshi, M.N.; Rudelli, R.D.; Biscotti, C.V.; Tubbs, R.R.; Layfield, L.J., 2003:
Predicting cervical lesions by INFORM HPV and Hybrid Capture II

Sims, C.; Krohn, M.; Caruana, R.; Meyn, L.; Rao, B.; Mitchell, T.; Schmuecking, I., 2000:
Predicting cesarean delivery Decision tree models

Mccrady, B.S.; Epstein, E.E.; Cook, S., 2003:
Predicting change in womens drinking Outcomes 12 months after treatment

Konforti, Boyana, 1999:
Predicting channel structures with genetics

Yang, W.Z.; Beauchemin, K.A., 2002:
Predicting chewing and ruminal pH by measuring physically effective NDF of dairy cow diets

Whitaker, R.C.; Chen, B.; Chamberlin, L.A., 2001 :
Predicting childhood obesity at birth

Dickinson, R.E., 2002:
Predicting climate change

Di Blasio, C.J.; Rhee, A.C.; Cho, D.; Scardino, P.T.; Kattan, M.W., 2003:
Predicting clinical end points: treatment nomograms in prostate cancer

Tzika, A.A.ia; Astrakas, L.G.; Zurakowski, D.; Young, T.P.ussaint; Goumnerova, L.; Anthony, D.C.; Black, P.M.l, 2003:
Predicting clinical grade of CNS tumors in children using non-invasive magnetic resonance spectroscopic imaging

Mohiddin, S.A.; Owens, D.; Tripodi, D.; S.P.ter, M.; Mcareavey, D.; Sachdev, V.; Plehn, J.; Fananapazir, L., 2003:
Predicting clinical outcome in hypertrophic cardiomyopathy associated with beta-myosin mutations A novel strategy based on functional domain affected

Wilson, P.M., 1999:
Predicting cognitive anxiety in youth soccer players

Petersen, R.C.; Ivnik, R.J.; O'brien, P.C.; Jack, C.R.Jr; Tangalos, E.; Boeve, B.F.; Kokmen, E., 2000:
Predicting cognitive decline

Rege, K.; Tugcu, N.; Dordick, J.S.; Cramer, S.M., 2001:
Predicting column performance in displacement chromatography from high throughput screening batch experiments

Li, A.; Wheeler, P.G., 2001:
Predicting common bile duct stones before preoperative ERCP

Mack, Richard, N., 2001:
Predicting communities vulnerable to plant invasions

Su, T.; Guan, X.; Tang, Y.; Gu, G.; Wang, J., 2010:
Predicting competitive adsorption behavior of major toxic anionic elements onto activated alumina: a speciation-based approach

Monterosso, J.R.; Pettinati, H.M.; Lipkin, C.B.; Decker, K.B.; Volpicelli, J.R., 2000:
Predicting compliance in pharmacotherapy trials with a brief scale that measures attitudes towards treatment

Berg, E.P.; Ellersieck, M.R.; Asfaw, A.; Linville, M., 1999:
Predicting component pieces of pork carcasses is improved by differential analysis of the industrial electromagnetic scan curve

Jacobs, G.A., 2000:
Predicting computational properties of neuronal ensembles using a database of reconstructed neurons

Smart, O.S.; Coates, G.M.P.; Sansom, M.S.P.; Alder, G.M.; Bashford, C.L., 1999:
Predicting conductance properties for ion channel structures

Young Fadok, T.M.; Lee, H.W.; Darby, C.H., 2000:
Predicting conversion in laparoscopic colorectal surgery A logistic regression model

Liu, H.C.ih; Wang, P.N.ng; Lin, K.N.ng; Liu, C.Y.h; Hong, C.J.e, 2002:
Predicting conversion of questionable dementia to Alzheimer disease

Yee, S.Harrell.; Barron, M.G., 2010:
Predicting coral bleaching in response to environmental stressors using 8 years of global-scale data

Khan, S.S.; Tighiouart, H.; Raman, G.; Pereira, B.J.G., 2003:
Predicting cost among patients with chronic kidney disease

Roger, V.; Singh, M.; Reeder, G.S.; Jacobsen, S.J.; Killian, J.; Weston, S.A., 2001:
Predicting death after MI Are scores useful in the community? A population-based study in Olmsted County, MN

Saeed, I.; Rogers, C.A.; Ganesh, S.; Murday, A.J.; Steering Group, 2003:
Predicting death following lung transplantation Development of a prognostic model

Fahlman, A.; Kayar, S.R.; Tikuisis, P.; Lin, W.C.; Whitman, W.B., 2000:
Predicting decompression sickness risk from H2 dives using conventional vs biochemical decompression in pigs

Steininger, J.; Pasian, C., 2000:
Predicting development of Lilium using thermal units

Hmeidan, M.C.; Dryden, G.M.l; Mccosker, J.E., 2000:
Predicting digestibility in rusa deer stags with internal and external markers

Vaz, L.E.; Bern, C.; Haque, R.; Akhter, S.; Roy, S.; Amann, J.; Fox, L.; Ali, A.; Wagatsuma, Y.; Breiman, R.; Maguire, J.; Secor, W.E., 2003:
Predicting disease development and treatment success for visceral leishmaniasis

Grossfeld, G.D.; Latini, D.; Broering, J.M.; Li, Y.P.ng; Carroll, P.R.; Henning, J.M., 2001:
Predicting disease recurrence in high-risk patients undergoing radical prostatectomy using percent positive biopsies Results from CaPSURE

Carrington, E., 2001:
Predicting disturbance to mussel beds Physiological response to a variable wave climate

Trim, R.S.; Schuckit, M.A.; Smith, T.L., 2010:
Predicting drinking onset with discrete-time survival analysis in offspring from the San Diego prospective study

Weir, P.J., 1999:
Predicting drug class teratogenicity prospectively

Howgate, E.M.; Proctor, N.J.; Rostami Hodjegan, A.; Tucker, G.T., 2003:
Predicting drug clearance allowing for the influence of P-glycoprotein activity using SIMCYPTM

Zambrowicz, B.P.; Turner, C.Alexander.; Sands, A.T., 2003:
Predicting drug efficacy: knockouts model pipeline drugs of the pharmaceutical industry

Wrighton, S.A.; Ring, B.J., 1999:
Predicting drug interactions and pharmacokinetic variability with in vitro methods: the olanzapine experience

Adejare, A.; Ogunbadeniyi, A.M.; Day, M.S.Jr, 2002:
Predicting drug membrane permeability using Immobilized Artificial Membrane partition chromatography

Mcginnity, D.F.; Riley, R.J., 2001:
Predicting drug pharmacokinetics in Man from in vitro metabolism studies

McGinnity, D.F.; Riley, R.J., 2001:
Predicting drug pharmacokinetics in humans from in vitro metabolism studies

Robert, J.; Vekris, A.; Pourquier, P.; Bonnet, J., 2004:
Predicting drug response based on gene expression

Shobowale Bakre, M.; Hassan, C.; Ansari, A.; Duley, J.; Marinaki, A.; Meenan, J.; Seed, P.; Sanderson, J., 2000:
Predicting drug toxicity and non-response Azathioprine and thiopurine methyltransferase as a metabolic model

Ajay, 2002:
Predicting drug-likeness: why and how?

Groves, C.J.; Saunders, B.P.; Spigelman, A.D.; Phillips, R.K., 2001 :
Predicting duodenal cancer in patients with familial adenomatous polyposis

Lopez, M.J.mes; Squires, R.; Molmenti, E.P.; Roden, J., 2000:
Predicting duration of initial hospital stay Does the type of organ transplant or diagnosis at admission affect the duration of initial hospital stay?

Charlton, M.R.; Ruppert, K.; Belle, S.H.; Nathan, B.M.; Schafer, D.; Wiesner, R.H.; Detre, K.M.; Wei, Y.; Everhart, J.E., 2002:
Predicting early and long term patient and graft survival for liver transplant recipients with HCV infection Results of the NIDDK liver transplant database

Gavard, J.A.; Chaitman, B.R.; Sakai, S.; Stocke, K.; Danchin, N.; Erhardt, L.; Chi, E.; Jessel, A.; Gallo, R.; Theroux, P., 2003:
Predicting early coronary revascularization after an acute coronary syndrome

Malinchoc, M.; Kosberg, C.L.; Kamath, P.S., 2000:
Predicting early mortality in patients with cirrhosis of the liver

Mayzer, R.; Puttler, L.I.; Fitzgerald, H.E.; Zucker, R.A., 2002:
Predicting early onset of first alcohol use from behavior problem indicators in early childhood

Huebner, Cynthia, D., 2003:
Predicting early plant invasions in West Virginia public forests

Mundt, J.C.; King, M., 2003:
Predicting early treatment drop out using interactive voice response

Brembilla Perrot, B.; Houriez, P.; Claudon, O.; Beurrier, D.; Preiss, J.P., 1999:
Predicting effect of d,I-sotalol on ventricular tachycardia inducibility from the response of RR variability to drug

Badano,E.I.; Marquet,P.A.; Cavieres,L.A., 2010:
Predicting effects of ecosystem engineering on species richness along primary productivity gradients

Bradley, J.S.; Dudley, M.N.; Drusano, G.L., 2003:
Predicting efficacy of antiinfectives with pharmacodynamics and Monte Carlo simulation

Bluemmel, M.; Zerbini, E.; Fernandez Rivera, S.; Karsli, A.; Russell, J.R., 2002:
Predicting efficiency of microbial production in diets by in situ and in vitro degradation characteristics of diet ingredients

Stager, J.M.; Skube, J.; Tanner, D.A.; Winston, W.; Morris, H.H., 2001:
Predicting elite swim performance at the USA 2000 Olympic Swim Trials

Alessandrini, E.A.; Shaw, K.N.; Bilker, W.B.; Schwarz, D.F.; Schwartz, J.S.nford, 2002:
Predicting emergency department reliance in Medicaid newborns

Jacobs, G.A.; Pittendrigh, C.S., 2002:
Predicting emergent properties of neuronal ensembles using a database of individual neurons

Cazin, K.; Mookerjee, S.; Surmacz, C.; Till, M.; Rosenbaum, S.; Strohecker, K., 2000:
Predicting energy cost of upper body exercise in younger women

Hayes, A.M.; Cover, L.; Myers, J.; Kiratli, B.J., 2003:
Predicting energy expenditure using Flex-HR in individuals with spinal cord injury

Goldfarb Rumyantzev, A.; Shin, J.; Rodriguez, J.; Schwenk, M.; Rosenberg, C.; Kundeling, S.; Charytan, C.; Spinowitz, B., 1999:
Predicting erythropoietin effect on hematocrit using artificial neural networks

Hee Sun Suh; Kyung Won Shim; Jee Hyun Kang; Yong Woo Park; Lee Sang Hwa; Lee Hong Su, 2003:
Predicting factor of vascular endothelial dysfunction in healthy premenopausal obese women

Silviu Dan, F.; Thomson, B.; Melanson, M., 2003:
Predicting factors for development of work-related Caddis fly allergy

Lee, H.L.e; Kim, T.W.ok; Lee, S.C.eol, 1999:
Predicting factors for fragmentation of ureter stone by ESWL

Lakomy, E.A.; Stalke, P.; Witczak Malinowska, K.; Michalska, Z.; Gesing, M., 2000:
Predicting factors for thyroid disorders in chronic hepatitis C patients treated with interferon alpha

Chappard, C.; Roux, C.; Paillard, M.; Houillier, P., 2001:
Predicting factors of BMD variations induced by parathyroidectomy in primary hyperparathyroidism

Lee, Y.S.; Hong, Y.H.; Park, S.H., 2001:
Predicting factors of elevated admission blood pressure in acute ischaemic stroke

Iliou, M.C.; Fumeron, C.; Benoit, M.O.; Tuppin, P.; Calonge, V.M.noyo; Moatti, N.; Buisson, C.; Jacquot, C., 2000:
Predicting factors of increased cardiac troponins in chronic hemodialysis patients

Brasselet, C.; Perotin, S.; Garnotel, R.; Lafont, A.; Elaerts, J.; Gillery, P.; Metz, D., 2003:
Predicting factors of inflammatory response following non-drug eluting stent implantation

Gonzalez Baron, M.; Ordonez, A.; Morales, S.; Juan Vidal, O.; Gay, M.; Galan, A.; Montalar, J.; Camps, C.; Delgado, J.; Feyjoo, M., 1999:
Predicting factors to epoetin alpha treatment

Dinsmoor, M.; Brock, E., 2001:
Predicting failed trial of labor after previous cesarean section

Anand, G.; Fernandez, A.A.; Sorondo, B.M.; Friedenberg, F.K., 2003:
Predicting failure of metronidazole therapy in patients with clostridium difficile associated diarrhea

Lundin Olsson, L.; Jensen, J.; Nyberg, L.; Gustafson, Y.; Olsson, T., 2001:
Predicting falls among elderly people in residential care by fall risk factors and staffs global rating

Halonen, K.I.; Leppaniemi, A.K.; Lundin, J.E.; Puolakkainen, P.A.; Kemppainen, E.A.; Haapiainen, R.K., 2000:
Predicting fatal outcome in early phase of severe acute pancreatitis

Carbone, John, P., 2002:
Predicting fate and transport The pesticide root zone model

Susarla, S.; Bacchus, S.; Wolfe, L.; Harvey, G.; Mccutcheon, S., 1999:
Predicting field performance of herbaceous species for phytoremediation of perchlorate

Beals, D.I.; Harris, R.C.; Pollman, C., 2002:
Predicting fish mercury concentrations in Everglades marshes Handling uncertainty in the Everglades Mercury Cycling Model with a Monte Carlo approach

Cornish, R.M., 2000:
Predicting flexure with rigid gas-permeable contact lenses

Hayward, J.L.; Henson, S.M., 2002:
Predicting fluctuations of animal numbers in the field using low dimensional mechanistic mathematical models

Benner, Steven Albert, 1999:
Predicting folded structures of proteins

Zorc, J.J.; Li, Y.; Scarfone, R.J., 2002:
Predicting follow-up after an emergency department visit for asthma

Chow, S.; Mullan, B., 2010:
Predicting food hygiene. An investigation of social factors and past behaviour in an extended model of the Health Action Process Approach

Cohen, S.D., 2002:
Predicting forest ecosystems at risk to invasion of exotic forest pathogens in the USA

Gebreslasie,M.T.; Ahmed,F.B.; Aardt,J.A.N.van, 2010:
Predicting forest structural attributes using ancillary data and ASTER satellite data

Benjamin, L.R.; Hembry, J.K.; Bowtell, J.; Phelps, K.; Gray, D., 1999:
Predicting frequency distributions in crops of carrot and red beet

Livengood, K.J.; Drobney, R.D., 1999:
Predicting frequency effects on the zone of reception for the Anabat II bat detector

Greene, Duane, W., 1999:
Predicting fruit set and evaluating the effects of chemical thinners on apples

Mahon, N.G.; Codd, M.B.; Poloniecki, J.; Mccann, H.A.; Sugrue, D.D., 1999:
Predicting future mortality from acute myocardial infarction in a Western society considering population shift, present trends and risk factor intervention

Geithner, C.A.; Malina, R.M.; Stager, J.M.; Eisenmann, J.C.; Sands, W.A., 2002:
Predicting future success in sport Profiling and talent identification in young athletes

Schietgat, L.; Vens, C.; Struyf, J.; Blockeel, H.; Kocev, D.; Dzeroski, S., 2010:
Predicting gene function using hierarchical multi-label decision tree ensembles

Cordonnier, C.; Herbrecht, R.; Leverger, G.; Levy, A.; Leclerq, R.; Ghanassia, J.P.erre; Bastuji Garin, S., 2003:
Predicting gram-negative bacterial infections in febrile neutropenic patients Results of a French, prospective Study

Kinsman, S.L., 2002:
Predicting gross motor function in cerebral palsy

Scott, S.L.; Schaefer, A.L.; Kennedy, A.D.; Christopherson, R.J.; Tong, A.K.W.; Harrison, H., 2002:
Predicting growth efficiency in live animals using infrared thermography

Kroupina, M.G.; Johnson, D.E.; Iverson, S.L.; Good, A.F., 2003:
Predicting growth trajectories of post-institutionalized children

Turgeon, K.; Rodriguez, M.A., 2003:
Predicting habitat selection in juvenile Atlantic salmon by use of logistic regression and classification trees

Gordon, G.H.; Baker, L.H.; Avalos, K.; Debar, L.; James, K.; Larsen, G.C., 1999:
Predicting health care utilization in patients with chest pain Relative roles of psychiatric and coronary disease

Mcnair, M.; Vrieze, S.; Bacharach, D.; Bednarski, P., 2001:
Predicting heart rate and blood lactate in a roller ski Biathlon race using field test data

Perin, E.C.; Silva, G.; Sarmento Leite, R.; Howell, M.; Muthopillai, R.; Lambert, B.; Flamm, S., 2001:
Predicting hemodynamic data and presence of scar tissue from electromechanical mapping Correlation with cardiac magnetic resonance imaging

Sivilotti, M.L.A.; Yarema, M.C.; Juurlink, D.N.; Good, A.M.; Johnson, D.W., 2003:
Predicting hepatotoxicity following acetaminophen overdose A nomogram for the post-N-AC era

Saunders, G.; Mcleod, S., 1999:
Predicting home range size from the body mass or population densities of feral pigs, Sus scrofa

Macdonald, P.D.M.; Kardia, S.L.R.; Hawley, W.A.; Hightower, A.W.; Mcelroy, P.D.; Siri, J.G.; Ombok, M.; Lal, A.A.; Wilson, M.L., 2000:
Predicting house-level Anopheles densities in western Kenya using multivariable regression and geostatistical hot spot and cold spot methods

Welsh, W.J.; Zauhar, R.; Kholodovych, V.; Nagarajan, K.; Ai, N., 2003:
Predicting human and environmental toxicity of chemicals based on their shape and electrostatic features

Miners, J.O.; Smith, P.A.; Sorich, M.J.; McKinnon, R.A.; Mackenzie, P.I., 2004:
Predicting human drug glucuronidation parameters: application of in vitro and in silico modeling approaches

Hopkins, R.; Edwards, D.P., 2000:
Predicting human pharmacokinetic parameters using artificial neural networks

Johnson; Wolfgang, 2000:
Predicting human safety: screening and computational approaches

Park, Kevin, 2001:
Predicting human toxicity from animal models

Patil,N.G.; Rajput,G.S.; Nema,R.K.; Singh,R.B., 2010:
Predicting hydraulic properties of seasonally impounded soils

Marfatia, A.; Dave, C.; Sternfels, P.; Iqbal, J.; Ajayi, A.; Ford, J.; Salazar Schicchi, J., 2000:
Predicting hypercapnia in obstructive airway diseases using spirometry and lung volumes

Alessandrini, E.A.; Shaw, K.N.; Bilker, W.B.; Bell, L.M.; Schwarz, D.F.; Schwartz, J.S.nford, 2002:
Predicting immunization status in Medicaid newborns

Hogsett, W.E.; Tingey, D.T., 2002:
Predicting impacts of ozone on plants and ecosystems for setting national air quality standards

Nelson, K.; Boyko, E., 2003:
Predicting impaired glucose tolerance using common clinical information Data from NHANES III

Yu, P.; Egan, A.R.; Leury, B.J., 2000:
Predicting in sacco rumen degradation kinetics of raw and dry roasted faba beans and lupin seeds by laboratory techniques

Carey, R.B.; Vanpelt, L., 2000:
Predicting in vitro susceptibility patterns of beta hemolytic and viridans streptococci using the Dade MicroScan MICroSTREP panels

Bosco, A.P.; Rhem, R.; Dolovich, M.B., 2002:
Predicting in vivo aerosol delivery using simulated breathing patterns

Thomas, D.R.; Kamel, H.K.; Ali, A.S.; Morley, J.E., 1999:
Predicting in-hospital death in malnourished patients by body mass index at admission

Williams, J.K.; Veledar, E.; Abramson, J.; Burnette, J.; Mahoney, E.M., 2001:
Predicting in-hospital mortality for African American patients undergoing coronary artery bypass grafting

Mehta, R.H.; Hagan, P.G.; Suzuki, T.; Bossone, E.; Gilon, D.; Llovet, A.; Cooper, J.; Pape, L.; Armstrong, W.F.; Bruckman, D.; Nienaber, C.A.; Eagle, K.A., 2001:
Predicting in-hospital mortality in acute type A aortic dissection Lessons from the International Registry of Aortic Dissection

Vaughan, G.M.; Walker, S.C.; Cheney, D.M.; Goodwin, C.W., 1999:
Predicting increased fluid requirements during burn resuscitation

Imoedemhe, D.; Avila, F.; Holiva, N.; Masangcay, M., 1999:
Predicting individual oocyte fertilization during in-vitro fertilization A new technique

Seeger, J.D.; Walker, A.M.; Williams, P.L.; Sacks, F.M.; Saperia, G.M., 2002:
Predicting initiation of statin therapy at Fallon Community Health Plan Building a propensity score-matched cohort study

Parham, James, E., 2003:
Predicting instream habitat and reach occupancy for native Hawaiian stream fishes

Voss, L.D.; Jeffery, A.N.; Metcalf, B.S.; Mallam, K.M.; Kirkby, J.; Murphy, M.J.; Wilkin, T.J., 2002:
Predicting insulin resistance in contemporary children Genes, gestation or current weight? The Early Bird study

Rejmanek, M.; Reichard, S., 2001:
Predicting invaders

Kolar, C.S.; Lodge, D.M., 2000:
Predicting invading fishes in the Great Lakes What can be learned from past invasions?

Dabbs, D.J.; Pickeral, J.; Tung, M.Y.; Silverman, J.F., 1999:
Predicting invasion in stereotactic core biopsies of breast Qualitative differences of antibodies that detect myoepithelial cells

Drake, J.M.; Lodge, D.M.; Dwyer, G.; Drury, K.L.S., 2001:
Predicting invasion success Applying probabilistic models of population growth to invading species

Leung, B.; Drake, J.; Lodge, D.M., 2003:
Predicting invasions Propagule pressure and the gravity of the Allee effect

Gerlach, J.D.; Rice, K.J., 2002 :
Predicting invasiveness from field experiments using congeneric plant species

Leishman, Michelle, 2003:
Predicting invasiveness from plant traits The role of disturbance type

Mashl, R.J.y; Roy, R.; Jakobsson, E., 2002:
Predicting ion fluxes of homology modeled ion channels

Luciani, G.B.; Montalbano, G.; Casali, G.; Mazzucco, A., 1999:
Predicting late functional outcome after myocardial revascularization in ischemic cardiomyopathy

Bard, K.A., 2000:
Predicting lateral bias and affect from neonatal measures in chimpanzees

Kalaszi, A.; Farkas, O., 2003:
Predicting lead compounds using libraries of flexible molecules

Chu, C.; Collins, N.C.; Lester, N.P.; Shuter, B.J., 2000:
Predicting littoral zone temperatures

Feld, J.J.; E.A.hri, D.; Ayers, M.; Mazulli, T.; Tellier, R.; Heathcote, E.J.nny, 2003:
Predicting liver disease severity in E antigen negative chronic hepatitis B

Flichman, D.; Cello, J.; Castano, G.; Frider, B.; Campos, R.; Sookoian, S., 1999:
Predicting liver histology in HCV patients with persistently normal ALT Practical advantage of a new upper limit of normal ALT level

Silverstein, M.J.; Lagios, M.D.; Waisman, J.R.; Groshen, S.; Colburn, W.J.; Skinner, K.; Silberman, H.; Lewinsky, B.S.; Gamagami, P., 1999:
Predicting local recurrence after breast conservation in patients with ductal carcinoma in situ of the breast A comparison of margin width and the Van Nuys Prognostic Index

Johnson, M.D.; Weber, W.J.Jr; Keinath, T.M.chael, II, 2000:
Predicting long-term desorption kinetics of HOCs sequestered in soils and sediments by superheated water extraction and temperature programmed desorption

Schmidt, B.; Asztalos, E.; Roberts, R.S.; Tipp Investigators, 2002:
Predicting long-term outcome in extremely-low-birth-weight infants Do we really have to wait until a corrected age of 18 months?

Defilippi, C.; Tiblier, E.; Wasserman, S.S.; Sperger, H.; Smiley, M.M.; Henrich, W.L.; Badalamenti, J.; Light, P.D., 2001:
Predicting long-term risk of death and cardiac events in hemodialysis patients using markers of inflammation, myocardial injury or both

Mcgrath, C.; Caetano, R.; Ramisetty Mikler, S., 2003:
Predicting male alcohol use during intimate partner violence among couples in the United States

Cartmill, M.; Lemelin, P.; Schmitt, D., 2001:
Predicting mammalian walking gaits from optimized support polygons

Corkum, L.D.; Dolan, D.M.; Roy, M.J.; Wright, J.L., 2001:
Predicting mass emergence of Hexagenia adults in Lake Erie

Traustadottir, T.; Etnier, J.L.; Romero, D.H., 2000:
Predicting maximal oxygen consumption in healthy older adults, using a modified 800-m walk test

Rodd, D.W.; Broshears, P.; Harlow, T.; Enzler, D.; Wilson, G., 2001:
Predicting maximal strength using the Nicholas Manual Muscle Tester

Chmielewski, T.L.; Stackhouse, S.; Binder Macleod, S.A.; Johnson, C.D.; Snyder Mackler, L., 2000:
Predicting maximal voluntary isometric contraction of the quadriceps from submaximal contraction after ACL injury

Brawner, C.A.; Keteyian, S.J.; Ehrman, J.K., 2002:
Predicting maximum heart rate in patients with heart disease Influence of beta-adrenergic blockade therapy

Feen, E.S.; Suarez, J.I.; Zaidat, O.O.; Bonnyapisit, K.; Suri, M.F.reed K.; Kaminski, H.J.; Ruff, R.L., 2003:
Predicting mechanical ventilation in myasthenia gravis exacerbation

Niksa, S.; Fujiwara, N., 2003:
Predicting mercury speciation in coal-derived flue gases

Doss, R.C.; Risse, G.L.; Gates, J.R., 2000:
Predicting mesial temporal sclerosis in epilepsy patients using the WMS-III and traditional measures of learning and memory

Furuno, J.P.; Harris, A.D.; Zhu, J.; Mcgregor, J.C.; Wright, M.O.; Perencevich, E.N., 2003:
Predicting methicillin resistant Staphylococcus aureus and vancomycin resistant enterococci infection upon hospital admission

Hershberger, C.D.; Ellis, L.B.M.; Wackett, L.P., 1999:
Predicting microbial biodegradative metabolism

Rentz, D.M.; Michalska, K.; Faust, R.R.; Budson, A.E.; Scinto, L.F.M.; Sperling, R.A.; Daffner, K.R., 2001:
Predicting mild cognitive impairment in high-functioning elders

Dror, O.; Shulman-Peleg, A.; Nussinov, R.; Wolfson, H.J., 2004:
Predicting molecular interactions in silico: I. A guide to pharmacophore identification and its applications to drug design

Schneidman-Duhovny, D.; Nussinov, R.; Wolfson, H.J., 2004:
Predicting molecular interactions in silico: II. Protein-protein and protein-drug docking

Durkin, J.L.; Dowling, J.J., 2000:
Predicting moment of inertia of the human leg requires the use of an elliptical model

Alvarez, A.; Lama, R.; Algar, J.; Santos, F.; Briceño, J.; Aranda, J.L.; Baamonde, C.; Salvatierra, A., 2001:
Predicting mortality after lung transplantation

Charlton, M.; Ruppert, K.; Belle, S.; Everhart, J.; Schafer, D.; Bass, N.; Wiesner, R.H., 2002:
Predicting mortality following liver transplantation for HCV The NIDDK liver transplant database model

Mehta, R.H.; Sonnad, S.S.; Das, S.; Karavite, D.J.; Russman, P.L.; Kinney, C.; Bruckman, D.; Shea, M.J.; Eagle, K.A.; Deeb, G.M.chael, 1999:
Predicting mortality for aortic valve surgery?

Tharalson, E.F.; Gerkin, R.D.; Ramirez, F.C., 2003:
Predicting mortality for inpatients with cirrhosis the utility of child pugh and meld scores

Lima, E.Q.; Castro, I.; Zanetta, D.M.T.; Yu, L., 2001:
Predicting mortality in acute renal failure by severity scoring systems

Scussel-Lonzetti, L.; Joyal, F.; Raynauld, J-Pierre.; Roussin, Aé.; Rich, E.; Goulet, J-Richard.; Raymond, Y.; Senécal, J-Luc., 2002:
Predicting mortality in systemic sclerosis: analysis of a cohort of 309 French Canadian patients with emphasis on features at diagnosis as predictive factors for survival

Mehta, R.H.; Suzuki, T.; Hagan, P.G.; Bossone, E.; Armstrong, W.F.; Eagle, K.A.; Nienaber, C.A.; Maroto, L.C.; Gilon, D.; Cooper, J., 2001:
Predicting mortality in type B acute aortic dissections

Cunningham, J.A.; Kellner, J.D.; Ford Jones, E.L.; Pong Porter, S.; Argyris, K.; Low, D.E., 2000:
Predicting multidrug nonsusceptible streptococcus pneumoniae Amoxicillin is number 1

Umberger, B.R.; Nagano, A.; Gerritsen, K.G.M., 2001:
Predicting muscle power in simulated vertical jumping

Auge, R.M.; Moore, J.L.; Cho, K.H., 2002:
Predicting mycorrhizal effects on stomatal conductance

Arts, T.; Rijcken, J.M.; Bovendeerd, P.H.M.; Prinzen, F.W., 1999:
Predicting myofiber direction in the cardiac wall by mathematical modeling

Mittendorf, R.; Khoshnood, B.; Pryde, P.; Lee, K.S.n; Sriram, S., 2001:
Predicting neonatal serum ionized magnesium levels at delivery

Stanley, G.B.; Heiser, L.M.; Lau, B.; Dan, Y., 1999:
Predicting neuronal responses in the striate cortex with neural networks

Dardzinski, B.J.; Mauger, D.T.; Buckalew, A.R.; Towfighi, J.; Smith, M.B., 2001:
Predicting neuropathological damage with multislice T1-, T2-, and diffusion-weighted magnetic resonance imaging of hypoxia-ischemia in a neonatal rat model

Wadleigh, F.R.; Church, G.M., 2001:
Predicting new SNP correlations to drug response by generalization from known correlations

Barnes, R.; Raymond, S.N., 2002:
Predicting new planets in known extra-solar planetary systems

Buermeyer, C.M.; Wald, R.L.; Kaltman, S.; Temoshok, L.R., 2001:
Predicting non-adherence to antiretroviral medications in a sample of inner city HIV patients

Hill, R.P.; Gulyas, S.; Jang, A.; Waldron, J.; Zheng, H., 1999:
Predicting normal tissue radiosensitivity; comparison or techniques using human fibroblasts

Fairweather, H.; Beauchemin, K.A.; Koenig, K.M., 2001:
Predicting nutrient balance in the feedlot

Ashley, P.F.; Ellwood, R.P.; Worthington, H.V.; Davies, R.M., 2000:
Predicting occlusal caries using the Electronic Caries Monitor

Sutherland, S.E.; Goldman, H.B., 2003:
Predicting occult stress urinary incontinence Are simple office maneuvers enough?

Kovatchev, B.P.; Cox, D.J.; Gonder Frederick, L.A.; Clarke, W.L., 2003:
Predicting occurrence of severe hypoglycemia from routine self-monitoring blood glucose data

Cox, D.; Kovatchev, B.; Gonder Frederick, L.; Clarke, W., 2003:
Predicting occurrence of severe hypoglycemia over the next 24 hours based on SMBG data

Kawasaki, Yukihiko; Suzuki, Junzo; Suzuki, Hitoshi; Yamamoto, Tadashi; Nozawa, Yoshihiro, 2003:
Predicting of damage of endothelial cell by the expression of FB21 in each glomerulonephritis

Kawasaki, Yukihiko; Suzuki, Junzo; Nozawa, Ruriko; Suzuki, Hitoshi; Tago, Kiichiro, 2001:
Predicting of relapses by lipoprotein level in children with steroid-sensitive nephrotic syndrome

Thaler, I.; Shmueli, O., 2001:
Predicting of the outcome of labor by analysis of FHR records obtained within 7 days of delivery using classification and regression trees

Balsis, S.M.; Wolfson, A., 2001:
Predicting off-duty napping in medical residents

Schumacher, M.J.; Hjelmroos Koski, M.; O'rourke, M.K., 2004:
Predicting onset and severity of pollen seasons in a semi-arid climate

Zucker, R.A.; Jester, J.M.; Fitzgerald, H.E.; Puttler, L.I.; Wong, M.M., 2003:
Predicting onset of drinking from behavior at three years of age Influence of early child expectancies and parental alcohol involvement upon early first use

Rohlin, L.; Sabatti, C.; Liao, J.C., 2003:
Predicting operon and regulon structure in Archaeoglobus fulgidus using transcriptomic data

Kim, J.R.oun; Choi, Y.S.ong; Yoo, Y.J., 1999:
Predicting optimum pH of oxidoreductase

Pierce, K.B.; Urban, D.L., 2002:
Predicting optimum sampling strategies to capture species-environment interactions

Carr, R.; Geddes, J.; Withington, G.; Wu, F., 2003:
Predicting oscillations in microvascular networks

Ho, G.T.er; Mowat, C.; Goddard, C.; Fennell, J.; Shah, N.; Prescott, R.; Satsangi, J., 2003:
Predicting outcome and risk assessment in severe ulcerative colitis

Velarde, A.; Katz, R., 2000:
Predicting outcome in acute respiratory distress syndrome in children

Stone, S.P.; Allder, S.J.; Gladman, J.R., 2000:
Predicting outcome in acute stroke

Dickinson, A.M.; Middleton, P.G., 2000:
Predicting outcome in allogeneic stem cell transplants Analysis of cytokine gene polymorphisms and a predictive human skin explant model for graft versus host disease

Jacinto, S.J.; Gieron-Korthals, M.; Ferreira, J.A., 2001:
Predicting outcome in hypoxic-ischemic brain injury

Alexopoulos, E.; Gionanlis, L.; Leontsini, M.; Papayianni, E.; Memmos, D., 2003:
Predicting outcome in idiopathic rapidly progressive glomerulonephritis

Ballo, M.T.; Strom, E.A.; Singletary, S.E.; Theriault, R.L.; Buchholz, T.A.; Mcneese, M.D., 1999:
Predicting outcome in patients with locoregionally recurrent breast carcinoma after mastectomy

Mayer, C.L.; Miller, J.W.; Lewellen, B.; Cross, D.J.; Minoshima, S., 2003:
Predicting outcome of temporal lobe resection in medically refractory epilepsy Statistical mapping analysis of FDG-PET

Spilg, E.G.; Stott, D.J.; Rumley, A.; Bell, L.; Robertson, L.; Campbell, A.M.; Lowe, G.D.O., 1999:
Predicting outcome using haemostatic variables in ischaemic stroke and vascular dementia

Fukushima, N.; Ohtake, S.; Sawa, Y.; Takahashi, T.; Nishimura, M.; Hirata, N.; Nakata, S.; Shirakura, R.; Sato, H.; Koretsune, Y.; Hori, M.; Matsuda, H., 1999:
Predicting outcomes and management of candidates for heart transplantation

Dennis, M.L.; Scott, C.K.; Godley, M.D.; Funk, R., 2000:
Predicting outcomes in adult and adolescent treatment with case mix vs level of care Findings from the Drug Outcome Monitoring Study

Latini, R.; Wong, M.; Masson, S.; Barlera, S.; Staszewsky, L.; Salio, M.; Maggioni, A.P.; Anand, I.S.; Tognoni, G.; Cohn, J.N., 2003:
Predicting outcomes in chronic heart failure from short-term change in BNP as a surrogate end-point Val-HeFT data

Mohanraj, R.; Brodie, M.J., 2003:
Predicting outcomes in newly diagnosed epilepsy

Russell, P.T.; Behnke, E.J.; Baker, R.S.ott; Clark, K.E., 2003:
Predicting ovine pregnancy and fetal number using a simple progesterone assay

Kusumo,B.H.; Hedley,M.J.; Hedley,C.B.; Arnold,G.C.; Tuohy,M.P., 2010:
Predicting pasture root density from soil spectral reflectance field measurement

Klein, T.; Kristt, D.; Israeli, M.; Duquesnoy, R.J., 2004:
Predicting paternal immunization in women with recurrent spontaneous abortions HLAMatchmaker assessment of amino acid mismatches

Gracey, D.M.; Makris, A.; Collett, P.V.; Gillin, A.G., 2001:
Predicting patient outcome at the commencement of haemodialysis treatment

Basco, W.T.J.; Gilbert, G.E.; Mallin, R.; Brown, E.A.; Carey, M.E.; Blue, A.V., 2003:
Predicting patients satisfaction for first year medical students using admission measures of communication

Muller, M.D.; Wallace, D.G.; Smith, D.P.; Fountain, S.B., 2000:
Predicting pattern violations using serial position in rat sequential learning

Hartman, K.M.; Mccarthy, B.C., 2001:
Predicting patterns of community invasion and potential changes in forest succession by a non-indigenous shrub, Amur honeysuckle

Blades, E.; Kimes, D.; Levine, E.; Mathison, G.; Thani, H.; Lavoie, M., 2004:
Predicting pediatric asthma admissions for Barbados

Schafroth, H.; Monos, D.; Constantinescou, A.; Floudas, C., 2002:
Predicting peptide binding to HLA class II molecules via atomistic level modeling, solvation methods, and deterministic global optimization

Travis, S.E.; Grace, J.B., 2010:
Predicting performance for ecological restoration: a case study using Spartina alterniflora

Maruta, T.; Yamate, T.; Tahara, M.; Kato, R.; Horikoshi, M.; Nakamura, T.; Okada, S.; IImori, M.; Kato, M., 2000:
Predicting personality disorder traits with defense styles

Denslow, J.S.; Daehler, C.C.; Ansari, S.; Kuo, H.C.i, 2003:
Predicting pest plants in Hawaii and other tropical Pacific islands

Yates, S.R.; Papiernik, S.K.; Gan, J., 2001:
Predicting pesticide volatilization from bare soil surfaces

Zhou, S.; Kestell, P.; Paxton, J.W., 2002:
Predicting pharmacokinetics and drug interactions in patients from in vitro and in vivo models The experience with 5,6-dimethylxanthenone-4-acetic acid , an anti-cancer drug eliminated mainly by conjugation

Karle, J.M., 2000:
Predicting pharmacological and physiological properties of candidate antimalarial agents using calculated molecular electronic properties

Gretebeck, K.A.; Gretebeck, R.J., 2003:
Predicting physical activity behavior in different age groups of older adults

Leech, S.D.; Valdes, E.V.; D.L.nge, C.F.M., 2002:
Predicting phytate content of Ontario soybean samples by near infrared reflectance spectroscopy

Thompson, K.; Masters, G.J.; Brown, V.K.; Grime, P., 2001:
Predicting plant community response to climate change

Gasso,N.; Basnou,C.; Vila,M., 2010:
Predicting plant invaders in the Mediterranean through a weed risk assessment system

Stark, S.C.; Bunker, D.E.; Carson, W.P., 2003:
Predicting plant invasion in north American ecoregions A macroecological approach

Flanders, S.; Stein, J.; Shochat, G.; Sellers, K.; Holland, M.; Maselli, J.; Gonzales, R., 2002:
Predicting pneumonia in adults with acute cough illness using a rapid c-reactive protein test

Aungst, Bruce, 2003:
Predicting poor permeability and formulation approaches to overcome it

Frankel, M.R.; Morgenstern, L.B.; Kwiatkowski, T.; Lu, M.; Tilley, B.C.; Broderick, J.P.; Libman, R.; Levine, S.R.; Brott, T., 2000:
Predicting poor prognosis after acute ischemic stroke An analysis of the placebo group from the NINDS rt-PA Stroke trial

Butler,C.D.; Trumble,J.T., 2010:
Predicting population dynamics of the parasitoid Cotesia marginiventris resulting from novel interactions of temperature and selenium

Ellis, A.M.; Post, E., 2003:
Predicting population response to climate change A non-linear modeling approach

Prevolnik,M.; Candek-Potokar,M.; Skorjanc,D., 2010:
Predicting pork water-holding capacity with NIR spectroscopy in relation to different reference methods

Cavazzoni, E.; Meehan, M.D.; Shackleton, C.; Sher, L.; Nissen, N.; Vierling, J.; Martin, P.; Poordad, F.; Tran, T.; Ayoub, W.; Colquhoun, S., 2003:
Predicting post-transplant survival with Hepatocellular carcinoma An assessment of current staging systems and individual parameters

Borchert, M.; Schreiner, D.; Knowd, T.; Plumb, T., 2002:
Predicting postfire survival in Coulter pine and gray pine after wildfire in central California

Milani, T.; Chacko George, G.; Hans Nuss, H.; Kim, M.; Walker, L.O.; Freeland Graves, J.H., 2002:
Predicting postpartum weight retention

Wang,X.Y.; Huang,X.L.; Jiang,L.Y.; Qiao,G.X., 2010:
Predicting potential distribution of chestnut phylloxerid based on GARP and Maxent ecological niche models

D.T.it, R.; Situ, P.; Simpson, T.; Fonn, D., 2001:
Predicting preference for monovision and bifocal contact lens wear Results from a one year clinical trial

Liu, P.Y.; Turner, L.; Conway, A.J.; Wishart, S.; Handelsman, D.J., 2001:
Predicting pregnancy and spermatogenesis by survival analysis during gonadotropin treatment of gonadotropin deficient infertile men

Muller,J.G.; Ogneva-Himmelberger,Y.; Lloyd,S.; Reed,J.M., 2010:
Predicting prehistoric taro Loi distribution in Hawaii

Stonecipher, K.G.; Malosky, T., 1999:
Predicting presbyopia based on preoperative computed topography

Msall, M.E.; Vohr, B.R.; Tremont, M.R.; Tucker, R.J.; Hogan, D.P., 2001:
Predicting preschool functional outcomes in self-care, mobility, and cognition after extreme prematurity Impact of neonatal and social risks

Gelfand, J.M.; Margolis, D.J.; Knauss, J.; Bilker, W., 2002:
Predicting pressure ulcers at home

Hardy, I.J.; Adkin, D.A., 2003 :
Predicting process behaviour using physicochemical data A computational approach

Kavanagh, T.; Mertens, D.J.; Hamm, L.F.; Beyene, J.; Kennedy, J.; Shephard, R.J., 2002:
Predicting prognosis in 2,380 women referred for cardiac rehabilitation

LiVolsi, V.A.; Baloch, Z.W., 2002:
Predicting prognosis in thyroid carcinoma: can histology do it?

Burney, I.A.; Salam, A.; Orakzai, S.H.; Orakzai, R.H.; Sharieff, S., 2002:
Predicting prognosis in unresectable hepatocellular carcinoma

Kavanagh, T.; Mertens, D.J.; Hamm, L.F.; Beyene, J.; Kennedy, J.; Nixon, D.; Thacker, L.; Shephard, R.J., 2000:
Predicting prognosis in women referred for cardiac rehabilitation

Valentine, A.; Ritchie, J.L.; Nevin, G.B.; Mckeown, S.R., 2001:
Predicting progression and survival in bladder cancer Use of p27Kip1 and epidermal growth factor receptor

Chertkow, H.M.; Verret, L.; Bergman, H.; Wolfson, C.; Mckelvey, R., 2001:
Predicting progression to dementia in elderly subjects with Mild Cognitive Impairment A multidisciplinary approach

Escobar, G.; Shaheen, S.; Yoshida, C.; Breed, E.; Botas, C.; Newman, T., 2003:
Predicting prolonged assisted ventilation in newborns gtoreq34 weeks

Bright, J.N.; Woolf, T.B.; Hoh, J.H., 2001:
Predicting properties of intrinsically unstructured proteins

Porter, C.R.; Crawford, E.D.vid; Bartsch, G.; Presti, J.C.J.; Tewari, A.; Gamito, E.J.; O'donnell, C.; Horninger, W., 2004:
Predicting prostate biopsy outcome An international prospective multicenter model involving 4,788 men

Hayward, Steven, 2000:
Predicting protein domain motions

Marcotte, Edward, M., 2002:
Predicting protein function and networks on a genomewide scale

Foreman, K.W.; Dill, K.A.; Phillips, A.T.; Rosen, J.B., 1999:
Predicting protein native states Minimization methods and models

Casadio, Rita, 2003:
Predicting protein structure The test case of TGAses

von Grotthuss, M.; Wyrwicz, L.S.; Pas, J.; Rychlewski, L., 2004:
Predicting protein structures accurately

Moult, J., 1999:
Predicting protein three-dimensional structure

Doss, R.C.; Gates, J.R.; Hawkins, J.L., 2001:
Predicting psychogenic nonepileptic seizures in an inpatient epilepsy program

Ferguson, Mark, K., 2000:
Predicting pulmonary complications after esophagectomy for cancer

Armbrecht, A.M.; Findlay, C.; Kaushal, S.; Aspinall, P.; Hill, A.R.; Dhillon, B., 2001:
Predicting quality of life outcome following cataract surgery in patients with age-related macular degeneration

Aydogan, B.; Bolch, W.E.; Morabito, B.J.; Marshall, D.T.; Wilson, K.E., 1999:
Predicting radiation damage at the molecular level with applications to radiation therapy

Sangar, V.K.; Collis, S.J.; Hendry, J.H.; Clarke, N.W.; Margison, G.P., 2001:
Predicting radiosensitivity of urological tumours using a Rapid Dual-Fluorescence Assay for DNA misrepair

Crozier, Lisa, G., 2003:
Predicting range shifts in response to climate change Studying a butterfly using convolution integrals

Hirsch, L.J.; Claassen, J.; Spencer, H.T.; Buchsbaum, R.; Adams, D.J.; Bazil, C.W.; Resor, S.R.J., 2003:
Predicting rash from lamotrigine Results from review of 812 patients

Passe, D.H.; Petrie, H.; Costigan, E.; Horswill, C.; Horn, M.; Murray, R., 2002:
Predicting rate of fluid loss during exercise using a multiple regression formula

Scharff, L.V.; Ahumada, A.J., 2001:
Predicting readability of transparent text on textured backgrounds

Hughes, D.A.; Walley, T., 2003:
Predicting "real world" effectiveness by integrating adherence with pharmacodynamic modeling

Block, J.P.; Fisher, W.P.; Devine, J.A.; Morris, J.; Yeoman, A.; Desalvo, K.B., 2002:
Predicting receipt of government benefits using health status measures

Firsching, R., 2003:
Predicting recovery

Rabbani, F.; Stapleton, A.M.; Wheeler, T.M.; Kattan, M.W.; Scardino, P.T., 2000:
Predicting recovery of erectile potency after radical prostatectomy Influence of age, preoperative potency, and extent of nerve-sparing

Konaka, R.; Imai, K.; Goto, S.; Nakajima, T.; Minai, K.; Ishikawa, K.; Hayafune, N.; Muto, M.; Ogawa, H.; Suwa, J.; Sugawa, A.; Horie, T., 2000:
Predicting recovery of global left ventricular function by the combination of single tracer, thallium, and quantitative gated SPECT Compared with dual tracers, BMIPP and Tl, technique

Swinburn, J.M.; Lahiri, A.; Senior, R., 2000:
Predicting recovery of myocardial function using early and delayed myocardial contrast echocardiography after acute myocardial infarction

Lewison, R.; Heppell, S., 2003:
Predicting recovery patterns in short and long-lived organisms

Burke, H.B.; Bauer, J.J.; Moul, J.W., 1999:
Predicting recurrence in early detected prostate cancer using p53

Barnes, N.; Boland, G.; Khavari, S.; Cramer, A.; Knox, W.F.; Bundred, N.J., 2004:
Predicting recurrence risk in DCIS The role of Type 1 tyrosine kinase receptor co-expression

Hoque, A.; Lippman, S.M.; Atkinson, N.; Boiko, I.; Sneige, N.; Sahin, A.; Sabichi, A.L.; Weber, D.; Lagios, M.; Schwarting, R.; Colburn, W.; Dhingra, K.; Kelloff, G.; Silverstein, M.; Boone, C.; Hittelman, W.N., 1999:
Predicting recurrent ductal carcinoma in situ of the breast Nuclear image analysis feature

Hermann, A.P.; Mosekilde, L.; Danish Osteoporosis Prevention Study (Dops), 1999:
Predicting regional and total BMD in perimenopausal women Very limited value of anthropometric measurements apart from bodyweight

Ito, K.; Tanaka, Y.; Orito, E.; Hirashima, N.; Mukaide, M.; Ide, T.; Sata, M.; Ueda, R.; Mizokami, M., 2003:
Predicting relapse after cessation of lamivudine monotherapy for chronic hepatitis B virus infection-application of newly developed HBV real-time detection direct test

Moore, B.A.; Budney, A.J., 2002:
Predicting relapse following successful outpatient marijuana treatment

Kumar, A.; Van't Hof, R.J.; Whiting, P.H.; Catto, G.R.D.; Ralston, S.H., 1999:
Predicting renal allograft dysfunction by monitoring nitric oxide production indirectly

Erturk, S.; Ishani, A.; Hertz, M.; Swanson, C.; Savik, K.; Rosenberg, M.E., 2000:
Predicting renal outcome following lung or heart/lung transplantation

Donoghue, Dan, J., 1999:
Predicting residue transfer into egg yolks

Pfeiffer, F.A.; Lupton, C.J.; Kuykendall, B.A., 2001:
Predicting resistance to compression of wool fibers

Zlobec, I.; Vuong, T.; Compton, C.; Zlobec, S., 2003:
Predicting response of invasive rectal cancer to brachytherapy by mathematical modeling of p21, bcl-2 and p53 immunohistochemistry

Nekulova, M.; Pecen, L.; Kalabova, R.; Simickova, M.; Vondracek, V.; Valik, D., 2001:
Predicting response of ovarian cancer to paclitaxel treatment Mathematical modelling based on trend analysis of CA125, TPS and thymidine kinase

Delgado Aros, S.; Cremonini, F.; Bredenoord, A.J.; Camilleri, M., 2003:
Predicting response to cholecystectomy by cck cholescintigraphy in patients with suspected functional biliary pain a meta analysis

Hu, R.J.; Malhotra, A.K.; Pickar, D., 1999:
Predicting response to clozapine Status of current research

Mchutchison, J.G.; Gordon, S.C.; Morgan, T.; Ling, M.H.; Gaurad, J.J.; Albrecht, J.; Dienstag, J., 1999:
Predicting response to initial therapy with interferon alfa during ribavirin in chronic hepatitis C using serum HCV RNA during therapy

Schweitzer, J.B.; Lee, D.; Tagamets, M.A.; Kilts, C.D., 2001:
Predicting response to methylphenidate in ADHD Correlates between rCBF and behavior

Beresford, T.P.; Clapp, L.K.; Arciniegas, D.B., 2003:
Predicting response to methylphenidate in Central Pontine Myelinolysis

Rosell, R.; Felip, E., 2001:
Predicting response to paclitaxel/carboplatin-based therapy in non-small cell lung cancer

Schofield, A.; Haites, N.E., 2000:
Predicting response to taxane chemotherapy in ovarian cancer The role of beta-tubulin gene mutations

Conwell, D.L.; Rice, T.; Dews, T.E.; Zuccaro, G.J.; Scheman, J.; Trolli, P.; Davies, S., 2003:
Predicting response to thorascopic splanchnicectomy in chronic pancreatic pain a prospective, exploratory pilot study

Ahn, C.; Sparks, R.E.; White, D.C., 2002:
Predicting responses of moist-soil plants to flood regime A simulation model to support restoration of the Illinois floodplain-river ecosystem

Torrentera, N.; Perez, H.; Zinn, R.A., 2002:
Predicting retail yield of crossbred bulls

Dionne, C.E.; Larocque, I.; Bourbonnais, R.; Fremont, P.; Rossignol, M.; Stock, S.R., 2004:
Predicting return to work in good health among workers with back pain who consult in primary care settings A 2-year prospective study

Glueck, T.; Blaas, S.; Grohmann, M.; Kiefmann, B.; Falk, W.; Straub, R.; Schoelmerich, J., 2001:
Predicting risk for infections in patients receiving immunosuppressive therapy

Gotto, A.M.Jr; Whitney, E.; Stein, E.A.; Shapiro, D.R.; Clearfield, M.; Weis, S.; Watson, D.J.; Cook, J.R.; Beere, P.A.; Downs, J.R., 1999:
Predicting risk of first acute major coronary events in the Air Force/Texas Coronary Atherosclerosis Prevention Study

Francois, M.R.; Grivas, P.C.; Studnicki, J.; Harbison, R.D., 2003:
Predicting risk of hospital admissions using an air pollution model

Sabatine, M.S.; Mccabe, C.H.; Morrow, D.A.; Giugliano, R.P.; D.L.mos, J.A.; Antman, E.M., 2000:
Predicting risk of post-discharge events in unstable angina

Rico-Rico, A.; Droge, S.T.J.; Hermens, J.L.M., 2010:
Predicting sediment sorption coefficients for linear alkylbenzenesulfonate congeners from polyacrylate-water partition coefficients at different salinities

Cosgriff, Robert, J., 2003:
Predicting seed/seedling dynamics The non-Tarot card approach

Spencer, S.S.; Berg, A.T.; Vickrey, B.G.; Sperling, M.R.; Bazil, C.W.; Shinnar, S.; Langfitt, J.T.; Walczak, T.S.; Pacia, S.V.; Ebrahimi, N.; Frobish, D., 2003:
Predicting seizure outcome of anteromedial temporal lobectomy The multicenter epilepsy surgery Study

Marson, A.G.; Kim, L.; Johnson, A.L.; Jacoby, A.; Chadwick, D.W., 2004:
Predicting seizure recurrence with and without antiepileptic drug treatment following single seizures and for early epilepsy A predictive model from a multicentre randomized controlled trial

Mazza, C.B.; Tugcu, N.; Breneman, C.M.; Garde, S.; Cramer, S.M., 2001:
Predicting selectivity of proteins in ion exchange systems

Elangovan, A.E.; Wilson, M.; Knox, F.W.; Barr, L.; Bundred, N.J., 2001:
Predicting sentinel node involvement Manchester experience

Ball, W.P.; D'adamo, P.C.; Paraskewich, M.R.Jr; Bouwer, E.J., 2000:
Predicting sequestration effects for hydrophobic organic chemicals A mountain of research and a modicum of application

Wolfe, F.; Kong, S.X., 1999:
Predicting service utilization in a national sample of RA patients with a questionnaire-based disease activity scale, the QDAS

Gorelick, M.H.; Stevens, M.W.; Scribano, P.V., 2001:
Predicting short term outcomes of acute asthma

Angermayr, B.; Cejna, M.; Koenig, F.; Karnel, F.; Gschwantler, M.; Pidlich, J.; Kreil, A.J.; Wichlas, M.; Lammer, J.; Gangl, A.; Peck Radosavljevic, M., 2002:
Predicting short-term survival after tips Meld vs child-pugh score

Griffith,A.B.; Alpert,H.; Loik,M.E., 2010:
Predicting shrub ecophysiology in the Great Basin Desert using spectral indices

Whellan, D.J.; Tuttle, R.H.; Shaw, L.K.; Jollis, J.G.; O'connor, C.M.; Borges Neto, S., 2004:
Predicting significant coronary artery disease in heart failure patients

Marshall, C.; Griffiths, P.A.; E.S.eemy, M.; Eremin, O., 2003:
Predicting significant residual tumour upon completion of neoadjuvant chemotherapy, using tumour to background ratios and 99mTc Sestamibi scintimammography prior to the commencement of neoadjuvant chemotherapy

User, H.M.; Jain, P.; Mcvary, K.T., 2002:
Predicting sildenafil effectiveness using intraoperative cavermap stimulation

Sakai, S.; Chaitman, B.R.; Gavard, J.A.; Stocke, K.; Danchin, N.; Erhardt, L.; Gallo, R.; Theroux, P., 2001:
Predicting six month mortality in acute coronary syndromes Results from the GUARDIAN Trial

Seliem, R.M.; Istvanic, S.; March, D.; Coughlin, B.; Goulart, R.A.; Bur, M.E., 2002:
Predicting size of residual ductal carcinoma in-situ by evaluation of mammotome breast biopsies

Roche, F.; Pichot, V.; Sforza, E.; Duverney, D.; Garet, M.; Barthelemy, J.C., 2003:
Predicting sleep apnea from the heart period A time-frequency domain analysis

Garzon, M.B.nito; Ruiz, J.M.ldonado; Sanchez, D.D.os, R.; Sainz Ollero, H., 2003:
Predicting spanish sclerophyllous forests potentiality using artificial neural networks

Rosentrater,K.A.; Lehman,R.M., 2010:
Predicting stability of distillers wet grains with color analysis

Tan, S.K.; Malina, R.M., 2003:
Predicting static muscular strength from anthropometry in a sample with a history of chronic undernutrition

Downes, G.; Knowles, L.; Ilic, J., 2003:
Predicting stiffness in Douglas-fir wood A comparison of acoustic and SilviScan estimates with static bending data

Holtrop, A.M.rie; Dolan, C.R.; Austen, D.; Smogor, R., 2003:
Predicting stream-sampling effort required to adequately assess index of biotic integrity Part I

Dolan, C.R.; Holtrop, A.M.; Austen, D.J.; Smogor, R.A., 2003:
Predicting stream-sampling effort required to adequately assess index of biotic integrity Part II

Chaikin, D.C.; Romanzi, L.; Menezes, A.; Rosenthal, J.; Weiss, J.P.; Blaivas, J.G., 1999:
Predicting stress incontinence in continent women with severe genital prolapse

Rasmussen, A.; Annan, J., 2010:
Predicting Stress Related to Basic Needs and Safety in Darfur Refugee Camps: A Structural and Social Ecological Analysis

Gompertz, P.; Tan, G., 1999:
Predicting stroke outcome using G-score3

Fischer, D.; Eisenberg, D., 1999:
Predicting structures for genome proteins

Morales, P.A.; Heuser, R.R.; Weirick, E.A.; Hatler, C.W., 2002:
Predicting success in crossing chronic total occlusions with a new guidewire

Chapa, J.; Hibbard, J.; Naccasha, N.; Ismail, M., 2001:
Predicting successful induction of labor in patients with previous cesarean section

Richter, A.; Blaha, L.; Gross, W.; Schreiber, W., 2003:
Predicting successful job performance of schizophrenics after discharge from hospital

Wold, A.L.; Whitmore, E.A.; Mikulich, S.K.; Hall, S.K.; Crowley, T.J., 2002:
Predicting suicidal behavior in adolescents with conduct and substance use problems

Kong, D.F.; Shaw, L.K.; Harrell, F.E.Jr; Muhlbaier, L.H.; Lee, K.L.; Califf, R.M.; Jones, R.H., 2002:
Predicting survival from the coronary arteriogram An experience-based statistical index of coronary artery disease severity

Topouzi, M.; Kovacs, L.; Shrier, I.; Papageorgiou, A., 2003:
Predicting survival in VLBW infants The importance of birth weight and postnatal age

Neumann, R.M.; Cheng, L.; Leibovich, B.C.; Ramnani, D.M.; Weaver, A.L.; Nehra, A.; Zincke, H.; Bostwick, D.G., 2000 :
Predicting survival in bladder cancer patients treated by radical cystectomy

Kong, D.F.; Del Carlo, C.H.; Eisenstein, E.L., 1999:
Predicting survival in coronary disease Machine-learning computer models versus expert clinicians

Frimat, L.; Hallonet, P.; Chanliau, J.; Huu, T.C.o; Kessler, M., 2000:
Predicting survival in patients starting dialysis after 75 years of age A French monocentric experience

Bambha, K.; Dell'era, A.; Abraldes, J.G.; Turnes, J.; Garcia Pagan, J.C.rlos; Thostenson, J.; Kamath, P.S.; Kim, W.R.; Bosch, J., 2003:
Predicting survival in portal hypertension HVPG, Child-Pugh, or MELD?

Harrer, S.; Kullak Ublick, G.A.; Kadry, Z.; Clavien, P.A.; Renner, E.L.; Mullhaupt, B., 2001:
Predicting survival of patients on the liver transplant waiting list in Zurich Retrospective comparison between the Child-Turcotte-Pugh - and model for end-stage liver disease - scores

Ostertag, R.; Silver, W.L.; Lugo, A.E., 2001:
Predicting susceptibility to damage following hurricanes in a subtropical moist forest

Jones, M.P.; Ebert, C.C.; Schettler, A.; Crowell, M.D., 2003:
Predicting symptom scores for abdominal pain, bloating and nausea in controls and PTS with functional dyspepsia A psychophyiologic regression model

Acker, C.D.; Haas, J.S.; Kopell, N.; White, J.A., 2001:
Predicting synchrony in the oscillatory stellate cells of the entorhinal cortex

Wong, S.L.; Zhang, L.O.; Goldberg, D.S.; Tong, A.H.; Lesage, G.; Vidal, M.; Andrews, B.; Bussey, H.; Boone, C.; Roth, F.P., 2003:
Predicting synthetic lethality from a diverse collection of gene and protein relationships

Bork, Peer, 2000 :
Predicting targets for structural genomics

Zhao, Q.; Kho, A.; Kenney, A.M.; Yuk, D.; Golub, T.R.; Kohane, I.; Zhang, Y.; Rowitch, D.H., 2001:
Predicting temporal-spatial gene expression in neuronal progenitors using oligonucleotide microarrays

Stephenson, A.J.; D.B.asio, C.J.; Eastham, J.A.; Scardino, P.T.; Kattan, M.W., 2004:
Predicting the 10-year probability of prostate cancer recurrence An updated postoperative nomogram and a suite of nomograms for patients who are free of disease at one to five years after radical prostatectomy

Thomasson, K.A.; Lowe, S.L.; Pierce, K.S.; Czlapinski, J.; Kie, G., 2001:
Predicting the UV pi-pi* circular dichroism spectrum of cyclo 3

Durkaya,A.; Durkaya,B.; Cakil,E., 2010:
Predicting the above-ground biomass of crimean pine stands in Turkey

Kelly, R.F.; Thomas, J.T.; Hashim, A.S.; Albasha, K.; Thomas, S.J.; Parrillo, J.E.; Calvin, J.E., 2000:
Predicting the absence of coronary disease in patients with systolic heart failure of unclear etiology

Bai, C.; Kinahan, P.E.; Brasse, D.; Comtat, C.; Townsend, D.W.; Defrise, M., 2001:
Predicting the appearance of whole-body PET oncology images that are not corrected for attenuation

Helz, George, R., 2002:
Predicting the behavior of hazardous metals in sulfidic waters; importance of sulfur activity

Jones, O.; Green, T.; Houston, B., 2000:
Predicting the biological fate of methacrylate esters in rats using physiologically based pharmacokinetic modelling and quantitative structure property relationships

Hawthorne, A.; Butterwick, R.F., 2000:
Predicting the body composition of cats Development of a zoometric measurement for estimation of percentage body fat in cats

Cateau, H.; Kitano, K.; Fukai, T., 2001:
Predicting the consequence of any spike-timing-dependent learning

Christiansen, C.L.; Wang, F.; Barton, M.B.; Kreuter, W.; Elmore, J.G.; Gelfand, A.E.; Fletcher, S.W., 1999:
Predicting the cumulative risk of false-positive mammograms for individual women

Hallworth, S.P.; Fernando, R.; Stocks, G.M., 2002:
Predicting the density of bupivacaine and bupivacaine-opioid combinations

Chow, M.Y.; Goh, M.H., 2001:
Predicting the depth of double-lumen tubes

Coombs, R.W.; Brambilla, D.; Sampoleo, R.; Jack, M.; Dragavon, J.; Hammer, S.; Demeter, L., 2000:
Predicting the detection of HIV-1 RNA after a negative result on the standard Roche HIV-1 MonitorTM assay

Kristo, D.A.; Johnson, S.J.; Samanez, E.; Eliasson, A.; Netzer, N.; Andrada, T.; Taylor, Y., 2001:
Predicting the diagnosis of upper airway resistance syndrome using total arousal index

Han, D.; Sun, D.W.; O'kiely, P., 2000:
Predicting the digestibility of the primary growth of a permanent grassland pasture

Schade, C.S.; Bonar, S., 2003:
Predicting the distribution and impact of exotic fish species in the American West

Wootton, B.C.; Bates, S.C.; Evans, D.O.; Schleifenbaum, P.C., 2003:
Predicting the distribution of brook trout in small headwater catchments on the precambrian shield of south-central Ontario

Abdel Hady, H.; Greisen, G., 2001:
Predicting the duration of NASAL-CPAP in preterm newborns