EurekaMag PDF full texts Chapter 60,118

Maznah, Z.; Halimah, M.; Shitan, M.; Kumar Karmokar, P.; Najwa, S. 2017: Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA). Plos one 12(1): E0166203

Langdon, R.; Docherty, P.D.; Schranz, C.; Chase, J.Geoffrey. 2017: Prediction of high airway pressure using a non-linear autoregressive model of pulmonary mechanics. Biomedical Engineering Online 16(1): 126

Sung Tae, H.; Deuk Jae, S.; Kyung Sook, Y.; Ki Choon, S.; Na Yeon, H.; Beom Jin, P.; Min Ju, K.; Sung Bum, C. 2017: Prediction of high-grade ureteral urothelial carcinoma on CT urography. British Journal of Radiology 90(1078): 20170159

Podda, G.M.; Grossi, E.; Palmerini, T.; Buscema, M.; Femia, E.A.; Della Riva, D.; de Servi, S.; Calabrò, P.; Piscione, F.; Maffeo, D.; Toso, A.; Palmieri, C.; De Carlo, M.; Capodanno, D.; Genereux, P.; Cattaneo, M. 2017: Prediction of high on-treatment platelet reactivity in clopidogrel-treated patients with acute coronary syndromes. International Journal of Cardiology 240: 60-65

Harada, T.L.; Saito, K.; Araki, Y.; Matsubayashi, J.; Nagao, T.; Sugimoto, K.; Tokuuye, K. 2018: Prediction of high-stage liver fibrosis using ADC value on diffusion-weighted imaging and quantitative enhancement ratio at the hepatobiliary phase of Gd-EOB-DTPA-enhanced MRi at 1.5 T. Acta Radiologica 59(5): 509-516

Ho-Le, T.P.; Center, J.R.; Eisman, J.A.; Nguyen, T.V.; Nguyen, H.T. 2017: Prediction of hip fracture in post-menopausal women using artificial neural network approach. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2017: 4207-4210

Palaniandy, K.; Haspani, M.Saffari.Mohammad.; Zain, N.Rose.Mohd. 2017: Prediction of Histological Grade and Completeness of Resection of Intracranial Meningiomas: Role of Peritumoural Brain Edema. Malaysian Journal of Medical Sciences: Mjms 24(3): 33-43

Singh, O.; Su, E.C.-Y. 2016: Prediction of HIV-1 protease cleavage site using a combination of sequence, structural, and physicochemical features. Bmc Bioinformatics 17(Suppl 17): 478

Hake, A.; Pfeifer, N. 2017: Prediction of HIV-1 sensitivity to broadly neutralizing antibodies shows a trend towards resistance over time. Plos Computational Biology 13(10): E1005789

Khalid, Z.; Sezerman, O.Ugur. 2018: Prediction of HIV Drug Resistance by Combining Sequence and Structural Properties. Ieee/Acm Transactions on Computational Biology and Bioinformatics 15(3): 966-973

Matsuda, F.; Tomita, A.; Shimizu, H. 2017: Prediction of Hopeless Peptides Unlikely to be Selected for Targeted Proteome Analysis. Mass Spectrometry 6(1): A0056

Ugalde, H.éc.; Yubini, M.ía.C.; Rozas, S.án.; Sanhueza, M.ía.I.; Jara, H.án. 2017: Prediction of hospital mortality of ST elevation myocardial infarction using TIMi score. Revista Medica de Chile 145(5): 572-578

Guven-Maiorov, E.; Tsai, C-Jung.; Ma, B.; Nussinov, R. 2017: Prediction of Host-Pathogen Interactions for Helicobacter pylori by Interface Mimicry and Implications to Gastric Cancer. Journal of Molecular Biology 429(24): 3925-3941

Wang, P.; Jiang, X.; Hu, J.; Huang, X.; Zhao, J.; Ahuja, R. 2017: Prediction of huge magnetic anisotropies in 5d transition metallocenes. Journal of Physics. Condensed Matter: An Institute of Physics Journal 29(43): 435802

Yamamoto, Y.; Välitalo, P.A.; Wong, Y.C.; Huntjens, D.R.; Proost, J.H.; Vermeulen, A.; Krauwinkel, W.; Beukers, M.W.; Kokki, H.; Kokki, M.; Danhof, M.; van Hasselt, J.G.C.; de Lange, E.C.M. 2018: Prediction of human CNS pharmacokinetics using a physiologically-based pharmacokinetic modeling approach. European Journal of Pharmaceutical Sciences: Official Journal of the European Federation for Pharmaceutical Sciences 112: 168-179

Hülsemann, F.; Koehler, K.; Wittsiepe, Jürgen.; Wilhelm, M.; Hilbig, A.; Kersting, M.; Braun, H.; Flenker, U.; Schänzer, W. 2017: Prediction of human dietary δ 15 N intake from standardised food records: validity and precision of single meal and 24-h diet data. Isotopes in Environmental and Health Studies 53(4): 356-367

Yuen, E.; Swanson, S.; Witkin, J.M. 2017: Prediction of human efficacious antidepressant doses using the mouse forced swim test. Pharmacology Biochemistry and Behavior 161: 22-29

Stoffel, N.U.; Zeder, C.; Fort, E.ïs.; Swinkels, D.W.; Zimmermann, M.B.; Moretti, D. 2017: Prediction of human iron bioavailability using rapid c-ELISAs for human plasma hepcidin. Clinical Chemistry and Laboratory Medicine 55(8): 1186-1192

Yoshimatsu, H.; Ishii, K.; Konno, Y.; Satsukawa, M.; Yamashita, S. 2017: Prediction of human percutaneous absorption from in vitro and in vivo animal experiments. International Journal of Pharmaceutics 534(1-2): 348-355

Yamamoto, S.; Karashima, M.; Arai, Y.; Tohyama, K.; Amano, N. 2017: Prediction of Human Pharmacokinetic Profile After Transdermal Drug Application Using Excised Human Skin. Journal of Pharmaceutical Sciences 106(9): 2787-2794

Notaro, M.; Schubach, M.; Robinson, P.N.; Valentini, G. 2017: Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods. Bmc Bioinformatics 18(1): 449

Kleinbeck, S.; Schäper, M.; Zimmermann, A.; Blaszkewicz, M.; Brüning, T.; van Thriel, C. 2017: Prediction of human sensory irritation due to ethyl acrylate: the appropriateness of time-weighted average concentration × time models for varying concentrations. Archives of Toxicology 91(9): 3051-3064

Tebes-Stevens, C.; Patel, J.M.; Jones, W.J.; Weber, E.J. 2017: Prediction of Hydrolysis Products of Organic Chemicals under Environmental pH Conditions. Environmental Science and Technology 51(9): 5008-5016

Yamauchi, K.; Enomoto, Y.; Otani, K.; Egashira, Y.; Iwama, T. 2018: Prediction of hyperperfusion phenomenon after carotid artery stenting and carotid angioplasty using quantitative DSA with cerebral circulation time imaging. Journal of Neurointerventional Surgery 10(6): 576-579

Shao, P.; Chen, B.-L.; Ding, L.P.; Luo, D.-B.; Lu, C.; Kuang, X.-Y. 2017: Prediction of hypervalent molecules: investigation on MnC (M = Li, Na, K, Rb and Cs; n = 1-8) clusters. Physical Chemistry Chemical Physics: Pccp 19(37): 25289-25297

Ladner, T.; Mühlmann, M.; Schulte, A.; Wandrey, G.; Büchs, J. 2017: Prediction of Escherichia coli expression performance in microtiter plates by analyzing only the temporal development of scattered light during culture. Journal of Biological Engineering 11: 20

Park, Y.W.; Han, K.; Ahn, S.S.; Bae, S.; Choi, Y.S.; Chang, J.H.; Kim, S.H.; Kang, S.-G.; Lee, S.-K. 2018: Prediction of IDH1-Mutation and 1p/19q-Codeletion Status Using Preoperative MR Imaging Phenotypes in Lower Grade Gliomas. AJNR. American Journal of Neuroradiology 39(1): 37-42

Guenther, P.L.; Stedman, D.H.; Lesko, J.M. 1996: Prediction of IM240 Mass Emissions Using Portable Exhaust Analyzers. Journal of the Air and Waste Management Association 46(4): 343-348

Permala, J.; Tarning, J.; Nosten, Fçois.; White, N.J.; Karlsson, M.O.; Bergstrand, M. 2017: Prediction of Improved Antimalarial Chemoprevention with Weekly Dosing of Dihydroartemisinin-Piperaquine. Antimicrobial Agents and ChemoTherapy 61(5)

Behrendt, S.; Bühringer, G.; Höfler, M.; Lieb, R.; Beesdo-Baum, K. 2017: Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood. Drug and Alcohol Dependence 179: 32-41

Calhoun, V.D.; Lawrie, S.M.; Mourao-Miranda, J.; Stephan, K.E. 2017: Prediction of Individual Differences from Neuroimaging Data. Neuroimage 145(Part B): 135-136

Storlie, C.B.; Branda, M.E.; Gionfriddo, M.R.; Shah, N.D.; Rank, M.A. 2018: Prediction of individual outcomes for asthma sufferers. Biostatistics 19(4): 579-593

Hagenah, J.; Werrmann, E.; Scharfschwerdt, M.; Ernst, F.; Metzner, C. 2016: Prediction of individual prosthesis size for valve-sparing aortic root reconstruction based on geometric features. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2016: 3273-3276

Hellman, T.; Kiviniemi, T.; Vasankari, T.; Nuotio, I.; Biancari, F.; Bah, A.; Hartikainen, J.; Mäkäräinen, M.; Airaksinen, K.E.Juhani. 2017: Prediction of ineffective elective cardioversion of atrial fibrillation: a retrospective multi-center patient cohort study. Bmc Cardiovascular Disorders 17(1): 33

Rekik, I.; Li, G.; Wu, G.; Lin, W.; Shen, D. 2015: Prediction of Infant MRi Appearance and Anatomical Structure Evolution using Sparse Patch-based Metamorphosis Learning Framework. Patch-Based Techniques in Medical Imaging: first International Workshop Patch-Mi 2015 Held in Conjunction with Miccai 2015 Munich Germany October 9 2015 Revised Selected Papers. Patch-Mi 9467: 197-204

Doğan, C.; Bayram, Z.üb.; Candan, Öz.; Omaygenç, O.; Yılmaz, F.; Acar, R.D.; Akbal, Öz.ür.Y.şa.; Kaymaz, C.; Özdemir, N. 2017: Prediction of infarct size using two-dimensional speckle tracking echocardiography in acute myocardial infarction. Echocardiography 34(3): 376-382

García-Tello, A.; Gimbernat, H.; Redondo, C.; Meilán, E.; Arana, D.M.; Cacho, J.; Dorado, J.F.; Angulo, J.C. 2018: Prediction of infection caused by extended-spectrum beta-lactamase-producing Enterobacteriaceae: development of a clinical decision-making nomogram. Scandinavian Journal of Urology 52(1): 70-75

Chrysostomou, C.; Partaourides, H.; Seker, H. 2017: Prediction of Influenza a virus infections in humans using an Artificial Neural Network learning approach. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2017: 1186-1189

Leonenko, V.N.; Ivanov, S.V. 2018: Prediction of influenza peaks in Russian cities: Comparing the accuracy of two SEIR models. Mathematical Biosciences and Engineering: Mbe 15(1): 209-232

Velez-Serrano, J.F.; Velez-Serrano, D.; Hernandez-Barrera, V.; Jimenez-Garcia, R.; Lopez de Andres, A.; Garrido, P.Carrasco.; Álvaro-Meca, A. 2017: Prediction of in-hospital mortality after pancreatic resection in pancreatic cancer patients: A boosting approach via a population-based study using health administrative data. Plos one 12(6): E0178757

Sefton, J.M.; Lohse, K.R.; McAdam, J.S. 2016: Prediction of Injuries and Injury Types in Army Basic Training, Infantry, Armor, and Cavalry Trainees Using a Common Fitness Screen. Journal of Athletic Training 51(11): 849-857

Keshtidar, M.; Behzadnia, B. 2017: Prediction of intention to continue sport in athlete students: a self-determination theory approach. Plos one 12(2): E0171673

Jiao, X.; Ranganathan, S. 2017: Prediction of interface residue based on the features of residue interaction network. Journal of Theoretical Biology 432: 49-54

Kiyohara, S.; Oda, H.; Miyata, T.; Mizoguchi, T. 2016: Prediction of interface structures and energies via virtual screening. Science Advances 2(11): E1600746

Chen, P.; Liu, C.; Burge, L.; Mahmood, M.; Southerland, W.; Gloster, C. 2008: Prediction of inter-residue contact clusters from hydrophobic cores. International Journal of Data Mining and Bioinformatics 2008: 703-708

Lee, M.; Kim, H.S.; Chung, H.H.; Kim, J.-W.; Park, N.H.; Song, Y.S. 2017: Prediction of intra-abdominal adhesions using the visceral slide test: a prospective observational study. European Journal of Obstetrics Gynecology and Reproductive Biology 213: 22-25

Mateus, Aé.; Gordon, L.J.; Wayne, G.J.; Almqvist, H.; Axelsson, H.; Seashore-Ludlow, B.; Treyer, A.; Matsson, Pär.; Lundbäck, T.; West, A.; Hann, M.M.; Artursson, P. 2017: Prediction of intracellular exposure bridges the gap between target- and cell-based drug discovery. Proceedings of the National Academy of Sciences of the United States of America 114(30): E6231-E6239

Ballestero, M.Fernando.Manzolli.; Frigieri, G.; Cabella, B.Caetano.Troca.; de Oliveira, S.Mascarenhas.; de Oliveira, R.Santos. 2017: Prediction of intracranial hypertension through noninvasive intracranial pressure waveform analysis in pediatric hydrocephalus. Child's Nervous System: Chns: Official Journal of the International Society for Pediatric Neurosurgery 33(9): 1517-1524

Shurkhina, E.S.; Polyanskaya, T.Y.; Zorenko, V.Y.; Nesterenko, V.M. 2017: Prediction of Intraoperative Blood Loss during Total Knee Arthroplasty in HCV+ and HCV- Patients with Hemophilia a. Bulletin of Experimental Biology and Medicine 162(5): 676-678

Kamogashira, T.; Iwasaki, S.; Kashio, A.; Kakigi, A.; Karino, S.; Matsumoto, Y.; Yamasoba, T. 2017: Prediction of Intraoperative CSF Gusher and Postoperative Facial Nerve Stimulation in Patients with Cochleovestibular Malformations Undergoing Cochlear Implantation Surgery. Otology and Neurotology: Official Publication of the American Otological Society American Neurotology Society and European Academy of Otology and Neurotology 38(6): E114-E119

Semiz, A.ğ; Akpak, Y.şa.K.; Yılanlıoğlu, N.C.; Babacan, A.; Gönen, G.ök.; Çam Gönen, C.; Asıliskender, M.; Karaküçük, S. 2017: Prediction of intraoperative nausea and vomiting in caesarean delivery under regional anaesthesia. Journal of International Medical Research 45(1): 332-339

Uehara, S.; Yoshida, S.; Tanaka, H.; Yasuda, Y.; Tanaka, H.; Kijima, T.; Yokoyama, M.; Ishioka, J.; Matsuoka, Y.; Saito, K.; Fujii, Y. 2018: Prediction of Intraoperative Urinary Collecting System Entry in Patients with Peripheral Renal Tumors Undergoing Partial Nephrectomy: Usefulness of Tumor-Centered Multiplanar Reconstruction. Urologia Internationalis 100(1): 85-91

Lin, Y.S.; Kerr, S.J.; Randolph, T.; Shireman, L.M.; Senn, T.; McCune, J.S. 2016: Prediction of Intravenous Busulfan Clearance by Endogenous Plasma Biomarkers Using Global Pharmacometabolomics. Metabolomics: Official journal of the Metabolomic Society 12(10)

Sy, S.; Zhuang, L.; Xia, H.; Beaudoin, M.-E.; Schuck, V.J.; Derendorf, H. 2017: Prediction of in vivo and in vitro infection model results using a semimechanistic model of avibactam and aztreonam combination against multidrug resistant organisms. Cpt: Pharmacometrics and Systems Pharmacology 6(3): 197-207

Cline, E.I.; Bicciato, S.; DiBello, C.; Lingen, M.W. 2002: Prediction of in vivo synergistic activity of antiangiogenic compounds by gene expression profiling. Cancer Research 62(24): 7143-7148

Tanashian, M.M.; Medvedev, R.B.; Evdokimenko, A.N.; Gemdzhian, É G.; Ckrylev, S.I.; Lagoda, O.V.; Krotenkova, M.V.; Suslin, A.S. 2017: Prediction of ischaemic lesions of the brain in reconstructive operations on internal carotid arteries. Angiologiia i Sosudistaia Khirurgiia 23(1): 59-66

Chow, E.J.; Chen, Y.; Hudson, M.M.; Feijen, E.A.M.; Kremer, L.C.; Border, W.L.; Green, D.M.; Meacham, L.R.; Mulrooney, D.A.; Ness, K.K.; Oeffinger, K.C.; Ronckers, C.éc.M.; Sklar, C.A.; Stovall, M.; van der Pal, H.J.; van Dijk, I.W.E.M.; van Leeuwen, F.E.; Weathers, R.E.; Robison, L.L.; Armstrong, G.T.; Yasui, Y. 2018: Prediction of Ischemic Heart Disease and Stroke in Survivors of Childhood Cancer. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology 36(1): 44-52

Ilário, C.R.S.; Azarpeyvand, M.; Rosa, V.; Self, R.H.; Meneghini, J.úl.R. 2017: Prediction of jet mixing noise with Lighthill's Acoustic Analogy and geometrical acoustics. Journal of the Acoustical Society of America 141(2): 1203

Ruff, A.; Fiolka, T.; Kostewicz, E.S. 2017: Prediction of Ketoconazole absorption using an updated in vitro transfer model coupled to physiologically based pharmacokinetic modelling. European Journal of Pharmaceutical Sciences: Official Journal of the European Federation for Pharmaceutical Sciences 100: 42-55

Kim, S-Yeon.; Ko, J-A.; Kang, B-Sik.; Park, H-Jin. 2018: Prediction of key aroma development in coffees roasted to different degrees by colorimetric sensor array. Food Chemistry 240: 808-816

Duan, Y.; Zhou, M.; Xiao, J.; Wu, C.; Zhou, L.; Zhou, F.; Du, C.; Song, Y. 2016: Prediction of key genes and mi RNAs responsible for loss of muscle force in patients during an acute exacerbation of chronic obstructive pulmonary disease. International Journal of Molecular Medicine 38(5): 1450-1462

Usha, S.; Selvaraj, S. 2016: Prediction of kinase-inhibitor binding affinity using energetic parameters. Bioinformation 12(3): 172-181

Alberola-Rubio, J.; Garcia-Casado, J.; Prats-Boluda, G.; Ye-Lin, Y.; Desantes, D.; Valero, J.; Perales, A. 2017: Prediction of labor onset type: Spontaneous vs induced; role of electrohysterography?. Computer Methods and Programs in Biomedicine 144: 127-133

Chor, C.Ming.; Poon, L.Chiu.Yee.; Leung, T.Yeung. 2019: Prediction of labor outcome using serial transperineal ultrasound in the first stage of labor. Journal of Maternal-Fetal and Neonatal Medicine: the Official Journal of the European Association of Perinatal Medicine the Federation of Asia and Oceania Perinatal Societies the International Society of Perinatal Obstetricians 32(1): 31-37

Kjertakov, M.; Dalip, M.; Hristovski, R.; Epstein, Y. 2016: Prediction of lactate threshold using the modified Conconi test in distance runners. Physiology International 103(2): 262-270

Choi, S.H.; Kang, D.H. 2017: Prediction of Late Enophthalmos Using Preoperative Orbital Volume and Fracture Area Measurements in Blowout Fracture. Journal of Craniofacial Surgery 28(7): 1717-1720

Ogawa, S.; Hida, J-Ichi.; Ike, H.; Kinugasa, T.; Ota, M.; Shinto, E.; Itabashi, M.; Okamoto, T.; Yamamoto, M.; Sugihara, K.; Watanabe, T. 2017: Prediction of lateral pelvic lymph node metastasis from lower rectal cancer using magnetic resonance imaging and risk factors for metastasis: Multicenter study of the Lymph Node Committee of the Japanese Society for Cancer of the Colon and Rectum. International journal of colorectal disease 32(10): 1479-1487

Abdelgawwad, I.M.; Al Hawary, A.A.; Kamal, H.M.; Al Maghawry, L.M. 2017: Prediction of left ventricular contractile recovery using tissue Doppler strain and strain rate measurements at rest in patients undergoing percutaneous coronary intervention. International Journal of Cardiovascular Imaging 33(5): 643-651

Kiran, V.S.; Tiwari, A. 2018: Prediction of left ventricular dysfunction after device closure of patent ductus arteriosus: proposal for a new functional classification. Eurointervention: Journal of Europcr in Collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology 13(18): E2124-E2129

Huttin, O.; Coiro, S.; Selton-Suty, C.; Juillière, Y.; Donal, E.; Magne, J.; Sadoul, N.; Zannad, F.; Rossignol, P.; Girerd, N. 2016: Prediction of Left Ventricular Remodeling after a Myocardial Infarction: Role of Myocardial Deformation: a Systematic Review and Meta-Analysis. Plos one 11(12): E0168349

Choo, C.C.; Harris, K.M.; Ho, R.C. 2019: Prediction of Lethality in Suicide Attempts: Gender Matters. Omega 80(1): 87-103

Viktorov, A.A.; Zharinov, G.M.; Neklasova, N.J.; Morozova, E.E. 2017: Prediction of life expectancy for prostate cancer patients based on the kinetic theory of aging of living systems. Advances in Gerontology 30(3): 356-362

Fuji, H.; Qi, F.; Qu, L.; Takaesu, Y.; Hoshino, T. 2017: Prediction of Ligand Binding Affinity to Target Proteins by Molecular Mechanics Theoretical Calculation. Chemical and Pharmaceutical Bulletin 65(5): 461-468

Turner, M.; Deeth, R.J.; Platts, J.A. 2017: Prediction of ligand effects in platinum-amyloid-β coordination. Journal of Inorganic Biochemistry 173: 44-51

Assis, C.; Ramos, R.S.; Silva, L.A.; Kist, V.; Barbosa, Márcio.H.P.; Teófilo, R.F. 2017: Prediction of Lignin Content in Different Parts of Sugarcane Using Near-Infrared Spectroscopy (NIR), Ordered Predictors Selection (OPS), and Partial Least Squares (PLS). Applied Spectroscopy 71(8): 2001-2012

Ramirez, T.; Strigun, A.; Verlohner, A.; Huener, H.-A.; Peter, E.; Herold, M.; Bordag, N.; Mellert, W.; Walk, T.; Spitzer, M.; Jiang, X.; Sperber, S.; Hofmann, T.; Hartung, T.; Kamp, H.; van Ravenzwaay, B. 2018: Prediction of liver toxicity and mode of action using metabolomics in vitro in HepG2 cells. Archives of Toxicology 92(2): 893-906

Small, B.G.; Wendt, B.; Jamei, M.; Johnson, T.N. 2017: Prediction of liver volume - a population-based approach to meta-analysis of paediatric, adult and geriatric populations - an update. Biopharmaceutics and Drug Disposition 38(4): 290-300

Salas, S.; Resseguier, N.; Blay, J.Y.; Le Cesne, A.; Italiano, A.; Chevreau, C.; Rosset, P.; Isambert, N.; Soulie, P.; Cupissol, D.; Delcambre, C.; Bay, J.O.; Dubray-Longeras, P.; Krengli, M.; De Bari, B.; Villa, S.; Kaanders, J.H.A.M.; Torrente, S.; Pasquier, D.; Thariat, J.O.; Myroslav, L.; Sole, C.V.; Dincbas, H.F.; Habboush, J.Y.; Zilli, T.; Dragan, T.; Khan R, K.; Ugurluer, G.; Cena, T.; Duffaud, F.; Penel, N.; Bertucci, F.; Ranchere-Vince, D.; Terrier, P.; Bonvalot, S.; Macagno, N.; Lemoine, C.; Lae, M.; Coindre, J.M.; Bouvier, C. 2017: Prediction of local and metastatic recurrence in solitary fibrous tumor: construction of a risk calculator in a multicenter cohort from the French Sarcoma Group (FSG) database. Annals of Oncology: Official Journal of the European Society for Medical Oncology 28(8): 1979-1987

Park, J.W.; Lee, S.W.; Kim, J.S.; Song, S.Y. 2017: Prediction of local control in early glottic carcinoma using the maximum standardised uptake value. Cancer Radiotherapie: Journal de la Societe Francaise de Radiotherapie Oncologique 21(3): 205-209

Murase, Y.; Izumi, K.; Ohkado, A.; Aono, A.; Chikamatsu, K.; Yamada, H.; Igarashi, Y.; Takaki, A.; Mitarai, S. 2018: Prediction of Local Transmission of Mycobacterium tuberculosis Isolates of a Predominantly Beijing Lineage by Use of a Variable-Number Tandem-Repeat Typing Method Incorporating a Consensus Set of Hypervariable Loci. Journal of clinical microbiology 56(1)

Boot, C.R.L.; van Drongelen, A.; Wolbers, I.; Hlobil, H.; van der Beek, A.J.; Smid, T. 2017: Prediction of long-term and frequent sickness absence using company data. Occupational Medicine 67(3): 176-181

Veenis, J.F.; Boiten, H.J.; van den Berge, J.C.; Caliskan, K.; Maat, A.P.W.M.; Valkema, R.; Constantinescu, A.A.; Manintveld, O.C.; Zijlstra, F.; van Domburg, R.T.; Schinkel, A.F.L. 2019: Prediction of long-term (> 10 year) cardiovascular outcomes in heart transplant recipients: Value of stress technetium-99m tetrofosmin myocardial perfusion imaging. Journal of Nuclear Cardiology: Official Publication of the American Society of Nuclear Cardiology 26(3): 845-852

Brouwer, W.P.; van der Meer, A.J.P.; Boonstra, A.; Plompen, E.P.C.; Pas, S.D.; de Knegt, R.J.; de Man, R.A.; Ten Kate, F.J.W.; Janssen, H.L.A.; Hansen, B.E. 2017: Prediction of long-term clinical outcome in a diverse chronic hepatitis B population: Role of the PAGE-B score. Journal of Viral Hepatitis 24(11): 1023-1031

Crook, S.; Frei, A.; Ter Riet, G.; Puhan, M.A. 2017: Prediction of long-term clinical outcomes using simple functional exercise performance tests in patients with COPD: a 5-year prospective cohort study. Respiratory Research 18(1): 112

Devore, E.E.; Fong, T.G.; Marcantonio, E.R.; Schmitt, E.M.; Travison, T.G.; Jones, R.N.; Inouye, S.K. 2017: Prediction of Long-term Cognitive Decline Following Postoperative Delirium in Older Adults. Journals of Gerontology. Series a Biological Sciences and Medical Sciences 72(12): 1697-1702

Masiá, M.; Padilla, S.; Moreno, S.; Barber, X.; Iribarren, J.A.; Del Romero, J.; Gómez-Sirvent, J.L.; Rivero, Mía.; Vidal, F.; Campins, A.A.; Gutiérrez, Félix. 2017: Prediction of long-term outcomes of HIV-infected patients developing non-AIDS events using a multistate approach. Plos one 12(9): E0184329

Latronico, N.; Minelli, C.; Eikermann, M. 2017: Prediction of long-term outcome subtypes in ARDS: first steps towards personalised medicine in critical care. Thorax 72(12): 1067-1068

Choi, Y.J.; Chang, J.E.; Chung, C.J.; Tahk, J.H.; Kim, K.-H. 2017: Prediction of long-term success of orthopedic treatment in skeletal Class IIi malocclusions. American Journal of Orthodontics and Dentofacial Orthopedics: Official Publication of the American Association of Orthodontists its Constituent Societies and the American Board of Orthodontics 152(2): 193-203

Hompland, I.; Bruland, Øyvind.Sverre.; Hølmebakk, T.; Poulsen, J.Peter.; Stoldt, S.; Hall, K.Sundby.; Boye, K. 2017: Prediction of long-term survival in patients with metastatic gastrointestinal stromal tumor: analysis of a large, single-institution cohort. Acta Oncologica 56(10): 1317-1323

Nguyen, H.Q.; Lin, J.; Kimoto, E.; Callegari, E.; Tse, S.; Obach, R.S. 2017: Prediction of Losartan-Active Carboxylic Acid Metabolite Exposure Following Losartan Administration Using Static and Physiologically Based Pharmacokinetic Models. Journal of Pharmaceutical Sciences 106(9): 2758-2770

Sinding, M.; Peters, D.A.; Frøkjær, J.B.; Christiansen, O.B.; Petersen, A.; Uldbjerg, N.; Sørensen, A. 2017: Prediction of low birth weight: Comparison of placental T2* estimated by MRi and uterine artery pulsatility index. Placenta 49: 48-54

Rejali, M.; Mansourian, M.; Babaei, Z.; Eshrati, B. 2017: Prediction of Low Birth Weight Delivery by Maternal Status and Its Validation: Decision Curve Analysis. International Journal of Preventive Medicine 8: 53

Sabour, S. 2017: Prediction of low birth weight: Methodological issues. Placenta 55: 101

Håkansson, P.är. 2017: Prediction of low-field nuclear singlet lifetimes with molecular dynamics and quantum-chemical property surface. Physical Chemistry Chemical Physics: Pccp 19(16): 10237-10254

Chen, F.; Sun, H.; Liu, H.; Li, D.; Li, Y.; Hou, T. 2017: Prediction of luciferase inhibitors by the high-performance MIEC-GBDT approach based on interaction energetic patterns. Physical Chemistry Chemical Physics: Pccp 19(15): 10163-10176

Lynch, C.M.; Abdollahi, B.; Fuqua, J.D.; de Carlo, A.R.; Bartholomai, J.A.; Balgemann, R.N.; van Berkel, V.H.; Frieboes, H.B. 2017: Prediction of lung cancer patient survival via supervised machine learning classification techniques. International Journal of Medical Informatics 108: 1-8

Tuomi, T.; Pasanen, A.; Leminen, A.; Bützow, R.; Loukovaara, M. 2017: Prediction of lymphatic dissemination in endometrioid endometrial cancer: Comparison of three risk-stratification models in a single-institution cohort. Gynecologic Oncology 144(3): 510-514

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Hirnschall, N.; Buehren, T.; Bajramovic, F.; Trost, M.; Teuber, T.; Findl, O. 2017: Prediction of postoperative intraocular lens tilt using swept-source optical coherence tomography. Journal of Cataract and Refractive Surgery 43(6): 732-736

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Vălenaş, S.P.; Szentágotai-Tătar, A.; Grafton, B.; Notebaert, L.; Miu, A.C.; MacLeod, C. 2017: Prediction of pre-exam state anxiety from ruminative disposition: the mediating role of impaired attentional disengagement from negative information. Behaviour Research and Therapy 91: 102-110

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Jansen, C.; Thiele, M.; Verlinden, W.; Krag, A.; Francque, S.; Trebicka, J. 2017: Prediction of presence of oesophageal varices just by shear-wave elastography of the liver and spleen. Liver International: Official Journal of the International Association for the Study of the Liver 37(9): 1406-1407

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Fathi, Y.; Barati, M.; Zandiyeh, M.; Bashirian, S. 2017: Prediction of Preventive Behaviors of the Needlestick Injuries during Surgery among Operating Room Personnel: Application of the Health Belief Model. International Journal of Occupational and Environmental Medicine 8(4): 232-240

Angstman, K.B.; Garrison, G.M.; Gonzalez, C.A.; Cozine, D.W.; Cozine, E.W.; Katzelnick, D.J. 2017: Prediction of Primary Care Depression Outcomes at Six Months: Validation of DOC-6 ©. Journal of the American Board of Family Medicine: Jabfm 30(3): 281-287

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Yamamoto, M.; Watanabe, K.; Fukuda, T.; Miura, O. 2017: Prediction of Prognosis for Patients with Diffuse Large B-Cell Lymphoma Refractory to or in First Relapse After Initial R-CHOP Therapy: A Single-Institution Study. Anticancer Research 37(5): 2655-2662

Gleason, D.F.; Mellinger, G.T.; Arduino, L.J.; Bailar, J.C.; Becker, L.E.; Berman, H.I.; Bischoff, A.J.; Byar, D.P.; Blackard, C.E.; Doe, R.P.; Elliot, J.S.; Haltiwanger, E.; Higgins, R.B.; Jorgens, J.; Kramer, H.C.; Lee, L.E.; Malament, M.; Mostofi, F.K.; Parry, W.L.; Rogers, L.S.; Ulm, A.Hardy.; Quiambao, V.R. 2017: Prediction of Prognosis for Prostatic Adenocarcinoma by Combined Histological Grading and Clinical Staging. Journal of urology 197(2S): S134-S139

Nakashima, A.; Moriuchi, T.; Mitsunaga, W.; Yonezawa, T.; Kataoka, H.; Nakashima, R.; Koizumi, T.; Shimizu, T.; Ryu, N.; Higashi, T. 2017: Prediction of prognosis of upper-extremity function following stroke-related paralysis using brain imaging. Journal of Physical Therapy Science 29(8): 1438-1443

Wise, E.S.; Stonko, D.P.; Glaser, Z.A.; Garcia, K.L.; Huang, J.J.; Kim, J.S.; Kallos, J.A.; Starnes, J.R.; Fleming, J.W.; Hocking, K.M.; Brophy, C.M.; Eagle, S.S. 2017: Prediction of Prolonged Ventilation after Coronary Artery Bypass Grafting: Data from an Artificial Neural Network. Heart Surgery Forum 20(1): E007-E014

Waheed, Y.; Safi, S.Z.; Najmi, M.H.; Aziz, H.; Imran, M. 2017: Prediction of promiscuous T cell epitopes in RNA dependent RNA polymerase of Chikungunya virus. Asian Pacific Journal of Tropical Medicine 10(8): 760-764

Gayet, M.; Mannaerts, C.K.; Nieboer, D.; Beerlage, H.P.; Wijkstra, H.; Mulders, P.F.A.; Roobol, M.J. 2018: Prediction of Prostate Cancer: External Validation of the ERSPC Risk Calculator in a Contemporary Dutch Clinical Cohort. European Urology Focus 4(2): 228-234

Bjurlin, M.A.; Rosenkrantz, A.B.; Sarkar, S.; Lepor, H.; Huang, W.C.; Huang, R.; Venkataraman, R.; Taneja, S.S. 2018: Prediction of Prostate Cancer Risk Among Men Undergoing Combined MRI-targeted and Systematic Biopsy Using Novel Pre-biopsy Nomograms That Incorporate MRI Findings. Urology 112: 112-120

Casteleiro, M.A.; Stevens, R.; Klein, J. 2017: Prediction of Proteases Involved in Peptide Generation. Methods in Molecular Biology 1574: 205-213

Crozier, T.W.M.; Tinti, M.; Larance, M.; Lamond, A.I.; Ferguson, M.A.J. 2017: Prediction of Protein Complexes in Trypanosoma brucei by Protein Correlation Profiling Mass Spectrometry and Machine Learning. Molecular and Cellular Proteomics: Mcp 16(12): 2254-2267

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Jiang, J.; Wang, N.; Chen, P.; Zheng, C.; Wang, B. 2017: Prediction of Protein Hotspots from Whole Protein Sequences by a Random Projection Ensemble System. International Journal of Molecular Sciences 18(7)

Tuncbag, N.; Keskin, O.; Nussinov, R.; Gursoy, A. 2017: Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information. Methods in Molecular Biology 1558: 255-270

Bosc, N.; Wroblowski, B.; Meyer, C.; Bonnet, P. 2017: Prediction of Protein Kinase-Ligand Interactions through 2.5D Kinochemometrics. Journal of Chemical Information and Modeling 57(1): 93-101

Schomburg, K.T.; Nittinger, E.; Meyder, A.; Bietz, S.; Schneider, N.; Lange, G.; Klein, R.; Rarey, M. 2017: Prediction of protein mutation effects based on dehydration and hydrogen bonding - a large-scale study. Proteins 85(8): 1550-1566

Ju, Z.; Cao, J.-Z. 2017: Prediction of protein N-formylation using the composition of k-spaced amino acid pairs. Analytical Biochemistry 534: 40-45

Ma, S.; Song, Q.; Tao, H.; Harrison, A.; Wang, S.; Liu, W.; Lin, S.; Zhang, Z.; Ai, Y.; He, H. 2019: Prediction of protein-protein interactions between fungus (Magnaporthe grisea) and rice (Oryza sativa L.). Briefings in Bioinformatics 20(2): 448-456

Wen, Y.-T.; Lei, H.-J.; You, Z.-H.; Lei, B.-Y.; Chen, X.; Li, L.-P. 2017: Prediction of protein-protein interactions by label propagation with protein evolutionary and chemical information derived from heterogeneous network. Journal of Theoretical Biology 430: 9-20

Yu, B.; Lou, L.; Li, S.; Zhang, Y.; Qiu, W.; Wu, X.; Wang, M.; Tian, B. 2017: Prediction of protein structural class for low-similarity sequences using Chou's pseudo amino acid composition and wavelet denoising. Journal of Molecular Graphics and Modelling 76: 260-273

Karczyńska, A.S.; Mozolewska, M.A.; Krupa, P.ł; Giełdoń, A.; Liwo, A.; Czaplewski, C. 2018: Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information. Proteins 86(Suppl 1): 228-239

Zhang, S.; Duan, X. 2018: Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC. Journal of Theoretical Biology 437: 239-250

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Grishin, D.V.; Pokrovskaya, M.V.; Podobed, O.V.; Gladilina, J.A.; Pokrovsky, V.S.; Aleksandrova, S.S.; Sokolov, N.N. 2017: Prediction of protein thermostability from their primary structure: the current state and development factors. Biomeditsinskaia Khimiia 63(2): 124-131

Dyer, F.J. 2018: Prediction of Psychiatric Hospitalization, Diagnoses, Arrests, and Violent Behavior Through Scored Drawings and Associations. Psychological Reports 121(1): 4-25

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Yang, Q.; Wang, Y.; Ban, X.; Wu, J.; Rong, D.; Zhao, Q.; Xie, C.; Zhang, R. 2017: Prediction of pulmonary metastasis in pulmonary nodules (≤10 mm) detected in patients with primary extrapulmonary malignancy at thin-section staging CT. La Radiologia Medica 122(11): 837-849

Choo, C.C.; Chew, P.K.H.; Ho, C.S.; Ho, R.C. 2017: Prediction of Quality of Life in Asian Patients with Schizophrenia: A Cross-sectional Pilot Study. Frontiers in Psychiatry 8: 198

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Park, I.J.; An, S.; Kim, S.-Y.; Lim, H.M.; Hong, S.-M.; Kim, M.-J.; Kim, Y.J.; Yu, C.S. 2017: Prediction of radio-responsiveness with immune-profiling in patients with rectal cancer. Oncotarget 8(45): 79793-79802

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Cuervo, K.; Villanueva, L.ón. 2018: Prediction of Recidivism with the Youth Level of Service/Case Management Inventory (Reduced Version) in a Sample of Young Spanish Offenders. International Journal of Offender Therapy and Comparative Criminology 62(11): 3562-3580

Gerede, D.M.şe.; Candemir, B.şa.; Vurgun, V.K.; Aghdam, S.M.; Acıbuca, A.; Özcan, Öz.ür.U.ş; Göksülük, H.üs.; Kervancıoğlu, C.; Erol, Çe. 2015: Prediction of recurrence after cryoballoon ablation therapy in patients with paroxysmal atrial fibrillation. Anatolian Journal of Cardiology 2015

Kang, S.Young.; Cheon, G.Jeong.; Lee, M.; Kim, H.Seung.; Kim, J-Weon.; Park, N-Hyun.; Song, Y.Sang.; Chung, H.Hoon. 2017: Prediction of Recurrence by Preoperative Intratumoral FDG Uptake Heterogeneity in Endometrioid Endometrial Cancer. Translational Oncology 10(2): 178-183

Cobo, J.; Merino, E.; Martínez, C.; Cózar-Llistó, A.; Shaw, E.; Marrodán, T.; Calbo, E.; Bereciartúa, E.; Sánchez-Muñoz, L.A.; Salavert, M.; Pérez-Rodríguez, M.T.; García-Rosado, D.ác.; Bravo-Ferrer, J.M.ía.; Gálvez-Acebal, J.; Henríquez-Camacho, C.és.; Cuquet, J.; Pino-Calm, B.; Torres, L.; Sánchez-Porto, A.; Fernández-Félix, B.M.; Romero, J.é; Muriel, A.; Giner, L.; Boix, V.; Ramos-Martínez, A.; Martínez, R.ío.; Martos, P.ón.; Arch, O.; Sardiña, C.; Aguirre, E.; Badía, C.; Boix, L.ía.; Perales, I.; De Santos-Castro, P.A.; Bratos-Pérez, M.A.; Cuellar, S.; González, E.; Soto, A.; Sousa, A.án.; Llinares, P.; Castelo, L.; Morales, I.; Sojo, J.ús.; Delgado-Iribarren, A.; Martí, C.; Vázquez, R.; Mairal, P. 2018: Prediction of recurrent clostridium difficile infection at the bedside: the GEIH-Cdi score. International Journal of Antimicrobial Agents 51(3): 393-398

Escobar, G.J.; Baker, J.M.; Kipnis, P.; Greene, J.D.; Mast, T.C.; Gupta, S.B.; Cossrow, N.; Mehta, V.; Liu, V.; Dubberke, E.R. 2017: Prediction of Recurrent Clostridium Difficile Infection Using Comprehensive Electronic Medical Records in an Integrated Healthcare Delivery System. Infection Control and Hospital Epidemiology 38(10): 1196-1203

Zhang, C.; Wang, Y.; Zhao, X.; Liu, L.; Wang, C.; Pu, Y.; Zou, X.; Pan, Y.; Wong, K.Sing.; Wang, Y. 2017: Prediction of Recurrent Stroke or Transient Ischemic Attack After Noncardiogenic Posterior Circulation Ischemic Stroke. Stroke 48(7): 1835-1841

Fowler, N.J.; Blanford, C.F.; Warwicker, J.; de Visser, S.P. 2017: Prediction of Reduction Potentials of Copper Proteins with Continuum Electrostatics and Density Functional Theory. Chemistry 23(61): 15436-15445

Yamazoe, Y.; Yoshinari, K. 2017: Prediction of regioselectivity and preferred order of metabolisms on CYP1A2-mediated reactions. Part 2: Solving substrate interactions of CYP1A2 with non-PAH substrates on the template system. Drug Metabolism and Pharmacokinetics 32(5): 229-247

Sabour, S. 2017: Prediction of rehabilitation needs after treatment of cervical cancer: a methodological mistake. Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer 25(7): 2041

Echeburúa, E.; Gómez, M.; Freixa, M. 2017: Prediction of Relapse After Cognitive-Behavioral Treatment of Gambling Disorder in Individuals with Chronic Schizophrenia: a Survival Analysis. Behavior Therapy 48(1): 69-75

Sletten, E.T.; Arnes, M.; Lysa, L.M.; Moe, B.T.; Straume, B.; Orbo, A. 2017: Prediction of Relapse After Therapy Withdrawal in Women with Endometrial Hyperplasia: a Long-term Follow-up Study. Anticancer Research 37(5): 2529-2536

Nakhjavani, M.; Abdollahi, S.; Farzanefar, S.; Abousaidi, M.; Esteghamati, A.; Naseri, M.; Eftekhari, M.; Abbasi, M. 2017: Prediction of Relapse from Hyperthyroidism following Antithyroid Medication Withdrawal using Technetium Thyroid Uptake Scanning. Endocrine Practice: Official Journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists 23(4): 466-470

Moreno, Z.; Paster, A. 2017: Prediction of Remediation of a Heterogeneous Aquifer: a Case Study. Ground Water 55(3): 428-439

Lee, J.W.; Park, J.S.; Park, K.B.; Yoo, G.H.; Kim, S.S.; Lee, S.M. 2017: Prediction of renal cortical defect and scar using neutrophil-to-lymphocyte ratio in children with febrile urinary tract infection. NUKLEARMEDIZIN. Nuclear Medicine 56(3): 109-114

Ball, K.; Jamier, T.; Parmentier, Y.; Denizot, C.; Mallier, A.; Chenel, M. 2017: Prediction of renal transporter-mediated drug-drug interactions for a drug which is an OAT substrate and inhibitor using PBPK modelling. European Journal of Pharmaceutical Sciences: Official Journal of the European Federation for Pharmaceutical Sciences 106: 122-132

Bar-Meir, M.; Kalisky, I.; Schwartz, A.; Somekh, E.; Tasher, D. 2018: Prediction of Resistance to Intravenous Immunoglobulin in Children with Kawasaki Disease. Journal of the Pediatric Infectious Diseases Society 7(1): 25-29

Kawaguchi, Y.; Saito, T.; Mitsunaga, T.; Terui, K.; Nakata, M.; Matsuura, G.; Kouchi, K.; Yoshida, H. 2018: Prediction of respiratory collapse among pediatric patients with mediastinal tumors during induction of general anesthesia. Journal of Pediatric Surgery 53(7): 1365-1368

Taraji, M.; Haddad, P.R.; Amos, R.I.J.; Talebi, M.; Szucs, R.; Dolan, J.W.; Pohl, C.A. 2017: Prediction of retention in hydrophilic interaction liquid chromatography using solute molecular descriptors based on chemical structures. Journal of Chromatography. a 1486: 59-67

Sun, M.-A.; Wang, Y.; Zhang, Q.; Xia, Y.; Ge, W.; Guo, D. 2017: Prediction of reversible disulfide based on features from local structural signatures. Bmc Genomics 18(1): 279

Bellavia, D.; Iacovoni, A.; Scardulla, C.; Moja, L.; Pilato, M.; Kushwaha, S.S.; Senni, M.; Clemenza, F.; Agnese, V.; Falletta, C.; Romano, G.; Maalouf, J.; Dandel, M. 2017: Prediction of right ventricular failure after ventricular assist device implant: systematic review and meta-analysis of observational studies. European Journal of Heart Failure 19(7): 926-946

Islamova, S.N.; Islamov, R.S. 2017: Prediction of Risk for Boys' Involvement in Drug use Based on Levels of Self-evaluations in Russia. Indian Journal of Psychological Medicine 39(3): 281-286

Wang, W.; Song, X-Tao.; Chen, Y-Dai.; Yang, X-Sheng.; Xu, F.; Zhang, M.; Tan, K.; Yuan, F.; Li, D.; Lyu, S-Zheng. 2016: Prediction of risk of cardiovascular events in patients with mild to moderate coronary artery lesions using naïve Bayesian networks. Journal of Geriatric Cardiology: Jgc 13(11): 899-905

Zhu, X.-R.; Zhang, Y.-P.; Bai, L.; Zhang, X.-L.; Zhou, J.-B.; Yang, J.-K. 2017: Prediction of risk of diabetic retinopathy for all-cause mortality, stroke and heart failure: Evidence from epidemiological observational studies. Medicine 96(3): E5894

Sun, S.P.; Lu, W.; Lei, Y.B.; Men, X.M.; Zuo, B.; Ding, S.G. 2017: Prediction of round window visibility in cochlear implantation with temporal bone high resolution computed tomography. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 52(8): 561-565

Furmanchuk, A.'o.; Saal, J.E.; Doak, J.W.; Olson, G.B.; Choudhary, A.; Agrawal, A. 2018: Prediction of seebeck coefficient for compounds without restriction to fixed stoichiometry: a machine learning approach. Journal of Computational Chemistry 39(4): 191-202

Fedele, T.; Ramantani, G.; Burnos, S.; Hilfiker, P.; Curio, G.; Grunwald, T.; Krayenbühl, N.; Sarnthein, J. 2017: Prediction of seizure outcome improved by fast ripples detected in low-noise intraoperative corticogram. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology 128(7): 1220-1226

Mikurova, A.V.; Rybina, A.V.; Skvortsov, V.S. 2016: Prediction of selective inhibition of neuraminidase from various influenza virus strains by potential inhibitors. Biomeditsinskaia Khimiia 62(6): 691-703

Yang, C.; Shen, Z.; Wu, L.; Tang, H.; Zhao, L.; Cao, F.; Sun, H. 2017: Prediction of self-assemblies of sodium dodecyl sulfate and fragrance additives using coarse-grained force fields. Journal of Molecular Modeling 23(7): 211

Ho, R.W.H.; Chang, W.C.; Kwong, V.W.Y.; Lau, E.S.K.; Chan, G.H.K.; Jim, O.T.T.; Hui, C.L.M.; Chan, S.K.W.; Lee, E.H.M.; Chen, E.Y.H. 2018: Prediction of self-stigma in early psychosis: 3-Year follow-up of the randomized-controlled trial on extended early intervention. Schizophrenia Research 195: 463-468

Sohn, J.A.; Kim, H.-S.; Oh, J.; Cho, J.-Y.; Yu, K.-S.; Lee, J.; Shin, S.H.; Lee, J.A.; Choi, C.W.; Kim, E.-K.; Kim, B.I.; Park, E.A. 2017: Prediction of serum theophylline concentrations and cytochrome P450 1A2 activity by analyzing urinary metabolites in preterm infants. British Journal of Clinical Pharmacology 83(6): 1279-1286

Ramos-Fernández, J.é M.; Moreno-Pérez, D.; Gutiérrez-Bedmar, M.; Hernández-Yuste, A.; Cordón-Martínez, A.M.ía.; Milano-Manso, G.; Urda-Cardona, A. 2017: Prediction of Severe Course in Infants with RSV Bronchiolitis under 6 Months. Spain. Revista Espanola de Salud Publica 91

Lind Malte, A.; Uldbjerg, N.; Wright, D.; Tørring, N. 2018: Prediction of severe pre-eclampsia/HELLP syndrome by combination of sFlt-1, CT-pro-ET-1 and blood pressure: exploratory study. Ultrasound in Obstetrics and Gynecology: the Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology 51(6): 768-774

Vázquez, C.; Orlova, M.ía.; Angriman, F.; Minatta, J.é N.; Scibona, P.; Verzura, M.ía.A.; Jáuregui, E.G.; Díaz de Arce, H.; Pallotta, M.ía.G.; Belloso, W.H. 2017: Prediction of severe toxicity in adult patients under treatment with 5-fluorouracil: a prospective cohort study. Anti-Cancer Drugs 28(9): 1039-1046

Come, P.C.; Riley, M.F.; Ferguson, J.F.; Morgan, J.P.; McKay, R.G. 1988: Prediction of severity of aortic stenosis: accuracy of multiple noninvasive parameters. American Journal of Medicine 85(1): 29-37

Wen, L.; Bowen, C.R.; Hartman, G.L. 2017: Prediction of Short-Distance Aerial Movement of Phakopsora pachyrhizi Urediniospores Using Machine Learning. Phytopathology 107(10): 1187-1198

Pandey, A.K.; Rajput, Y.S.; Singh, D.; Sharma, R. 2018: Prediction of shorter oligonucleotide sequences recognizing aflatoxin M1. Biotechnology and Applied Biochemistry 65(3): 397-406

Tuomi, T.; Pasanen, A.; Leminen, A.; Bützow, R.; Loukovaara, M. 2017: Prediction of Site-Specific Tumor Relapses in Patients with Stage I-Ii Endometrioid Endometrial Cancer. International Journal of Gynecological Cancer: Official Journal of the International Gynecological Cancer Society 27(5): 923-930

Leng, X'zi.; Wang, J.; Ji, H.; Wang, Q'geng.; Li, H.; Qian, X.; Li, F.; Yang, M. 2017: Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses. Chemosphere 180: 513-522

Gorai, K.; Inoue, K.; Saegusa, N.; Shimamoto, R.; Takeishi, M.; Okazaki, M.; Nakagawa, M. 2017: Prediction of Skin Necrosis after Mastectomy for Breast Cancer Using Indocyanine Green Angiography Imaging. Plastic and Reconstructive Surgery. Global Open 5(4): E1321

Wareing, B.; Urbisch, D.; Kolle, S.N.; Honarvar, N.; Sauer, U.G.; Mehling, A.; Landsiedel, R. 2017: Prediction of skin sensitization potency sub-categories using peptide reactivity data. Toxicology in Vitro: An International Journal Published in Association with Bibra 45(Part 1): 134-145

Zang, Q.; Paris, M.; Lehmann, D.M.; Bell, S.; Kleinstreuer, N.; Allen, D.; Matheson, J.; Jacobs, A.; Casey, W.; Strickland, J. 2017: Prediction of skin sensitization potency using machine learning approaches. Journal of Applied Toxicology: Jat 37(7): 792-805

McCowan, L.M.E.; Thompson, J.M.D.; Taylor, R.S.; Baker, P.N.; North, R.A.; Poston, L.; Roberts, C.T.; Simpson, N.A.B.; Walker, J.J.; Myers, J.; Kenny, L.C. 2017: Prediction of Small for Gestational Age Infants in Healthy Nulliparous Women Using Clinical and Ultrasound Risk Factors Combined with Early Pregnancy Biomarkers. Plos one 12(1): E0169311

Zhang, H.; Wu, P.; Yin, A.; Yang, X.; Zhang, M.; Gao, C. 2017: Prediction of soil organic carbon in an intensively managed reclamation zone of eastern China: a comparison of multiple linear regressions and the random forest model. Science of the Total Environment 592: 704-713

Schmidtke, R.; Schröder, D.; Menth, J.; Staab, A.; Braun, M.; Wagner, K.G. 2017: Prediction of solid fraction from powder mixtures based on single component compression analysis. International Journal of Pharmaceutics 523(1): 366-375

Yang, Y.; Mace, B.R.; Kingan, M.J. 2017: Prediction of sound transmission through, and radiation from, panels using a wave and finite element method. Journal of the Acoustical Society of America 141(4): 2452

Kellermann, T.S.; Mueller, M.; Carter, E.G.; Brooks, B.; Smith, G.; Kopp, O.J.; Wagner, J.L. 2017: Prediction of specific depressive symptom clusters in youth with epilepsy: the NDDI-E-Y versus Neuro-QOL SF. Epilepsia 58(8): 1370-1379

Marquez-Chin, C.; Atwell, K.; Popovic, M.R. 2017: Prediction of specific hand movements using electroencephalographic signals. Journal of Spinal Cord Medicine 40(6): 696-705

Fox, N.S.; Rebarber, A.; Klauser, C.K.; Peress, D.; Gutierrez, C.V.; Saltzman, D.H. 2010: Prediction of spontaneous preterm birth in asymptomatic twin pregnancies using the change in cervical length over time. American Journal of Obstetrics and Gynecology 202(2): 155.E1-4

Tanaka, K.; Yamada, K.; Matsushima, M.; Izawa, T.; Furukawa, S.; Kobayashi, Y.; Iwashita, M. 2017: Prediction of spontaneous preterm delivery in asymptomatic twin pregnancies using cervical length and granulocyte elastase. Taiwanese Journal of Obstetrics and Gynecology 56(2): 188-191

Chen, Y.; Geng, H.Y.; Yan, X.; Sun, Y.; Wu, Q.; Chen, X. 2017: Prediction of Stable Ground-State Lithium Polyhydrides under High Pressures. Inorganic Chemistry 56(7): 3867-3874

Archer, S.C.; Bradley, A.J.; Cooper, S.; Davies, P.L.; Green, M.J. 2017: Prediction of Streptococcus uberis clinical mastitis risk using Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) in dairy herds. Preventive Veterinary Medicine 144: 1-6

Tanaka, A.; Node, K. 2018: Prediction of Stroke After Cardiac Catheterization: no Reason, no Stroke. Journal of Atherosclerosis and Thrombosis 25(3): 221-223

Kang, D.-W.; Jeong, H.-G.; Kim, D.Y.; Yang, W.; Lee, S.-H. 2017: Prediction of Stroke Subtype and Recanalization Using Susceptibility Vessel Sign on Susceptibility-Weighted Magnetic Resonance Imaging. Stroke 48(6): 1554-1559

Janjić, G.V.; Milosavljević, M.D.; Veljković, D.Ž; Zarić, S.D. 2017: Prediction of strong O-H/M hydrogen bonding between water and square-planar Ir and Rh complexes. Physical Chemistry Chemical Physics: Pccp 19(13): 8657-8660

Fritz, B.G.; Aalseth, C.E.; Back, H.O.; Hayes, J.C.; Humble, P.H.; Ivanusa, P.; Mace, E.K. 2018: Prediction of sub-surface 37Ar concentrations at locations in the Northwestern United States. Journal of Environmental Radioactivity 181: 1-7

Bouman, C.; van Herwaarden, N.; van den Hoogen, F.; van der Maas, A.; van den Bemt, B.; den Broeder, A.A. 2017: Prediction of successful dose reduction or discontinuation of adalimumab, etanercept, or infliximab in rheumatoid arthritis patients using serum drug levels and antidrug antibody measurement. Expert Opinion on Drug Metabolism and Toxicology 13(6): 597-604

Mannil, M.; von Spiczak, J.; Hermanns, T.; Alkadhi, H.; Fankhauser, C.D. 2018: Prediction of successful shock wave lithotripsy with CT: a phantom study using texture analysis. Abdominal Radiology 43(6): 1432-1438

Sutker, P.B.; Newberry, W.M.; Bradham, G.B. 1978: Prediction of success in medical school. Journal of the South Carolina Medical Association 74(5): 255-259

Rizas, K.D.; McNitt, S.; Hamm, W.; Massberg, S.; Kääb, S.; Zareba, W.; Couderc, J.-P.; Bauer, A. 2017: Prediction of sudden and non-sudden cardiac death in post-infarction patients with reduced left ventricular ejection fraction by periodic repolarization dynamics: MADIT-Ii substudy. European Heart Journal 38(27): 2110-2118

Yamamoto, H.; Yamada, T.; Tamaki, S.; Morita, T.; Furukawa, Y.; Iwasaki, Y.; Kawasaki, M.; Kikuchi, A.; Kondo, T.; Ozaki, T.; Seo, M.; Sato, Y.; Ikeda, I.; Fukuhara, E.; Abe, M.; Nakamura, J.; Fukunami, M. 2019: Prediction of sudden cardiac death in patients with chronic heart failure by regional washout rate in cardiac MIBG SPECT imaging. Journal of Nuclear Cardiology: Official Publication of the American Society of Nuclear Cardiology 26(1): 109-117

Hallgren, K.A.; Ries, R.K.; Atkins, D.C.; Bumgardner, K.; Roy-Byrne, P. 2017: Prediction of Suicide Ideation and Attempt Among Substance-Using Patients in Primary Care. Journal of the American Board of Family Medicine: Jabfm 30(2): 150-160

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Chen, S.; Izgorodina, E.I. 2017: Prediction of 1H NMR chemical shifts for clusters of imidazolium-based ionic liquids. Physical Chemistry Chemical Physics: Pccp 19(26): 17411-17425

Ingrisch, M.; Schöppe, F.; Paprottka, K.; Fabritius, M.; Strobl, F.F.; De Toni, E.N.; Ilhan, H.; Todica, A.; Michl, M.; Paprottka, P.M. 2018: Prediction of 90Y Radioembolization Outcome from Pretherapeutic Factors with Random Survival Forests. Journal of Nuclear Medicine: Official Publication Society of Nuclear Medicine 59(5): 769-773

Amsler, M.; Naghavi, S.Shahab.; Wolverton, C. 2017: Prediction of superconducting iron-bismuth intermetallic compounds at high pressure. Chemical Science 8(3): 2226-2234

Ma, Y.; Duan, D.; Shao, Z.; Li, D.; Wang, L.; Yu, H.; Tian, F.; Xie, H.; Liu, B.; Cui, T. 2017: Prediction of superconducting ternary hydride MgGeH6: from divergent high-pressure formation routes. Physical Chemistry Chemical Physics: Pccp 19(40): 27406-27412

Periyasamy, M.; Cho, J.Young.; Ahn, S.; Han, H-Seong.; Yoon, Y-Seok.; Choi, Y.; Jang, J.Seong.; Kwon, S.Uk.; Kim, S.; Choi, J.Kyu.; Guro, H. 2017: Prediction of surgical outcomes of laparoscopic liver resections for hepatocellular carcinoma by defining surgical difficulty. Surgical Endoscopy 31(12): 5209-5218

Lee, S.M.; Seo, J.B.; Oh, S.Y.; Kim, T.H.; Song, J.W.; Lee, S.M.; Kim, N. 2018: Prediction of survival by texture-based automated quantitative assessment of regional disease patterns on CT in idiopathic pulmonary fibrosis. European Radiology 28(3): 1293-1300

Tuqan, W.'e.; Innabi, A.; Alawneh, A.; Farsakh, F.A.; Al-Khatib, M. 2017: Prediction of Survival Following Percutaneous Biliary Drainage for Malignant Biliary Obstruction. Journal of Translational Internal Medicine 5(2): 127-131

Tanaka, S.; Kanagawa, T.; Momma, K.; Hori, S.; Satoh, H.; Nagamatsu, T.; Fujii, T.; Kimura, T.; Sawada, Y. 2017: Prediction of sustained fetal toxicity induced by ketoprofen based on PK/PD analysis using human placental perfusion and rat toxicity data. British Journal of Clinical Pharmacology 83(11): 2503-2516

Aherrera, J.A.M.; Abola, M.T.B.; Balabagno, M.M.O.; Abrahan, L.L.; Magno, J.D.A.; Reganit, P.F.M.; Punzalan, F.E.R. 2016: Prediction of Symptomatic Embolism in Filipinos with Infective Endocarditis Using the Embolic Risk French Calculator. Cardiology Research 7(4): 130-139

Lokeskrawee, T.; Muengtaweepongsa, S.; Patumanond, J.; Tiamkao, S.; Thamangraksat, T.; Phankhian, P.; Pleumpanupat, P.; Sribussara, P.; Kitjavijit, T.; Supap, A.; Rattanaphibool, W.; Prisiri, J. 2017: Prediction of Symptomatic Intracranial Hemorrhage after Intravenous Thrombolysis in Acute Ischemic Stroke: the Symptomatic Intracranial Hemorrhage Score. Journal of Stroke and Cerebrovascular Diseases: the Official Journal of National Stroke Association 26(11): 2622-2629

Li, X.; Xu, Y.; Cui, H.; Huang, T.; Wang, D.; Lian, B.; Li, W.; Qin, G.; Chen, L.; Xie, L. 2017: Prediction of synergistic anti-cancer drug combinations based on drug target network and drug induced gene expression profiles. Artificial Intelligence in Medicine 83: 35-43

Fauchier, L.; Pericart, L.; Bourguignon, T.; Bernard, L.; Clementy, N.; Angoulvant, D.; Babuty, D.; Bernard, A. 2017: Prediction of Systemic Septic Embolism in Patients with Left-Sided Infective Endocarditis. Journal of the American College of Cardiology 69(15): 1992-1993

Chen, C.; Ji, X.; Xu, K.; Zhang, B.; Miao, L.; Jiang, J. 2017: Prediction of T- and H-Phase Two-Dimensional Transition-Metal Carbides/Nitrides and their Semiconducting-Metallic Phase Transition. Chemphyschem: a European Journal of Chemical Physics and Physical Chemistry 18(14): 1897-1902

Nayak, T.; Tinghe Zhang; Zijing Mao; Xiaojing Xu; Pack, D.J.; Bing Dong; Yufei Huang 2017: Prediction of temperature induced office worker's performance during typing task using EEG. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2017: 1684-1687

Kramer, T.; Huijgen, B.C.H.; Elferink-Gemser, M.T.; Visscher, C. 2017: Prediction of Tennis Performance in Junior Elite Tennis Players. Journal of Sports Science and Medicine 16(1): 14-21

Bunmahotama, W.; Hung, W.-N.; Lin, T.-F. 2017: Prediction of the adsorption capacities for four typical organic pollutants on activated carbons in natural waters. Water Research 111: 28-40

Messad, F.; Létourneau-Montminy, M.P.; Charbonneau, E.; Sauvant, D.; Guay, F. 2018: Prediction of the amino acid digestibility of legume seeds in growing pigs: a meta-analysis approach. Animal: An International Journal of Animal Bioscience 12(5): 940-949

Su, Q.; Lu, W.; Du, D.; Chen, F.; Niu, B.; Chou, K.-C. 2017: Prediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression. Oncotarget 8(30): 49359-49369

Sierra, J.; Roig, N.; Giménez Papiol, G.; Pérez-Gallego, E.; Schuhmacher, M. 2017: Prediction of the bioavailability of potentially toxic elements in freshwaters. Comparison between speciation models and passive samplers. Science of the Total Environment 605-606: 211-218

Poudel, K.K.; Huang, Z.; Neupane, P.R.; Steel, R. 2017: Prediction of the Cancer Incidence in Nepal. Asian Pacific Journal of Cancer Prevention: Apjcp 18(1): 165-168

Berndt, A.; Lanna, D.P.D.; da Cruz, G.M.; Tullio, R.R.; Sakamoto, L.S.; de Alencar, M.M. 2017: Prediction of the chemical body composition of Nellore and crossbreed bulls. Journal of Animal Science 95(9): 3932-3939

Marks, M.ł; Glinicki, M.ł A.; Gibas, K. 2015: Prediction of the Chloride Resistance of Concrete Modified with High Calcium Fly Ash Using Machine Learning. Materials 8(12): 8714-8727

Arakawa, Y.; Nai, Y.; Shidahara, M.; Furumoto, S.; Seki, C.; Okamura, N.; Tashiro, M.; Kudo, Y.; Yanai, K.; Gonda, K.; Watabe, H. 2017: Prediction of the Clinical SUV Ratio in Amyloid PET Imaging Using a Biomathematic Modeling Approach Toward the Efficient Development of a Radioligand. Journal of Nuclear Medicine: Official Publication Society of Nuclear Medicine 58(8): 1285-1292

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Nomura, N.; Miyajima, N.; Sazuka, T.; Tanaka, A.; Kawarabayasi, Y.; Sato, S.; Nagase, T.; Seki, N.; Ishikawa, K.; Tabata, S. 1994: Prediction of the coding sequences of unidentified human genes. I. the coding sequences of 40 new genes (KIAA0001-KIAA0040) deduced by analysis of randomly sampled cDNA clones from human immature myeloid cell line KG-1. Dna Research: An International Journal for Rapid Publication of Reports on Genes and Genomes 1(1): 27-35

Nagase, T.; Seki, N.; Ishikawa, K.; Tanaka, A.; Nomura, N. 1996: Prediction of the coding sequences of unidentified human genes. V. The coding sequences of 40 new genes (KIAA0161-KIAA0200) deduced by analysis of cDNA clones from human cell line KG-1 (supplement). Dna Research: An International Journal for Rapid Publication of Reports on Genes and Genomes 3(1): 43-53

Nagase, T.; Ishikawa, K.; Suyama, M.; Kikuno, R.; Hirosawa, M.; Miyajima, N.; Tanaka, A.; Kotani, H.; Nomura, N.; Ohara, O. 1999: Prediction of the coding sequences of unidentified human genes. XIII. the complete sequences of 100 new cDNA clones from brain which code for large proteins in vitro. Dna Research: An International Journal for Rapid Publication of Reports on Genes and Genomes 6(1): 63-70

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Nagase, T.; Kikuno, R.; Nakayama, M.; Hirosawa, M.; Ohara, O. 2000: Prediction of the coding sequences of unidentified human genes. XVIII. the complete sequences of 100 new cDNA clones from brain which code for large proteins in vitro. Dna Research: An International Journal for Rapid Publication of Reports on Genes and Genomes 7(4): 273-281

Nagase, T.; Ishikawa, K.; Kikuno, R.; Hirosawa, M.; Nomura, N.; Ohara, O. 1999: Prediction of the coding sequences of unidentified human genes. XV. the complete sequences of 100 new cDNA clones from brain which code for large proteins in vitro. Dna Research: An International Journal for Rapid Publication of Reports on Genes and Genomes 6(5): 337-345

Kwiecińska, K.; Kosicka-Gębska, Młgorzata.; Gębski, J.; Gutkowska, K. 2017: Prediction of the conditions for the consumption of game by Polish consumers. Meat Science 131: 28-33

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Cao, H.; Zhang, Y.; Zhao, J.; Zhu, L.; Wang, Y.; Li, J.; Feng, Y.-M.; Zhang, N. 2017: Prediction of the Ebola Virus Infection Related Human Genes Using Protein-Protein Interaction Network. Combinatorial Chemistry and High Throughput Screening 20(7): 638-646

Mistry, P.; Neagu, D.; Sanchez-Ruiz, A.; Trundle, P.R.; Vessey, J.D.; Gosling, J.P. 2017: Prediction of the effect of formulation on the toxicity of chemicals. Toxicology Research 6(1): 42-53

Borella, E.; Poggesi, I.; Magni, P. 2018: Prediction of the Effect of Renal Impairment on the Pharmacokinetics of new Drugs. Clinical Pharmacokinetics 57(4): 505-514

Avanesov, M.; Münch, J.; Weinrich, J.; Well, L.; Säring, D.; Stehning, C.; Tahir, E.; Bohnen, S.; Radunski, U.K.; Muellerleile, K.; Adam, G.; Patten, M.; Lund, G. 2017: Prediction of the estimated 5-year risk of sudden cardiac death and syncope or non-sustained ventricular tachycardia in patients with hypertrophic cardiomyopathy using late gadolinium enhancement and extracellular volume CMR. European Radiology 27(12): 5136-5145

Battut, I.B.; Kempfer, A.; Lemasson, N.; Chevrier, L.; Camugli, S. 2017: Prediction of the fertility of stallion frozen-thawed semen using a combination of computer-assisted motility analysis, microscopical observation and flow cytometry. Theriogenology 97: 186-200

Salminen, M.; Eloranta, S.; Vire, J.; Viikari, P.; Viikari, L.; Vahlberg, T.; Lehtonen, A.; Arve, S.; Wuorela, M.; Viitanen, M. 2018: Prediction of the Future Need for Institutional Care in Finnish Older People: A Comparison of Two Birth Cohorts. Gerontology 64(1): 19-27

Ryu, M.S.; Kim, H.G.; Kim, H.Y.; Min, K.-S.; Kim, H.J.; Lee, H.M. 2017: Prediction of the glass transition temperature and design of phase diagrams of butadiene rubber and styrene-butadiene rubber via molecular dynamics simulations. Physical Chemistry Chemical Physics: Pccp 19(25): 16498-16506

Kazsoki, A.; Szabó, P.ét.; Zelkó, R.án. 2017: Prediction of the hydroxypropyl cellulose-poly(vinyl alcohol) ratio in aqueous solution containing papaverine hydrochloride in terms of drug loaded electrospun fiber formation. Journal of Pharmaceutical and Biomedical Analysis 138: 357-362

Buckinx, F.; Croisier, J-Louis.; Reginster, J-Yves.; Lenaerts, Céline.; Brunois, Téo.; Rygaert, X.; Petermans, J.; Bruyère, O. 2018: Prediction of the Incidence of Falls and Deaths Among Elderly Nursing Home Residents: The SENIOR Study. Journal of the American Medical Directors Association 19(1): 18-24

Sciortino, G.; Rodríguez-Guerra Pedregal, J.; Lledós, Aí.; Garribba, E.; Maréchal, J-Didier. 2018: Prediction of the interaction of metallic moieties with proteins: An update for protein-ligand docking techniques. Journal of Computational Chemistry 39(1): 42-51

Oyama, T.; Inoue, H.; Arima, M.; Momma, K.; Omori, T.; Ishihara, R.; Hirasawa, D.; Takeuchi, M.; Tomori, A.; Goda, K. 2017: Prediction of the invasion depth of superficial squamous cell carcinoma based on microvessel morphology: magnifying endoscopic classification of the Japan Esophageal Society. Esophagus: official journal of the Japan Esophageal Society 14(2): 105-112

Ding, L.-P.; Shao, P.; Lu, C.; Zhang, F.-H.; Liu, Y.; Mu, Q. 2017: Prediction of the Iron-Based Polynuclear Magnetic Superhalogens with Pseudohalogen CN as Ligands. Inorganic Chemistry 56(14): 7928-7935

Simmonds, M.J.; Meiselman, H.J. 2016: Prediction of the level and duration of shear stress exposure that induces subhemolytic damage to erythrocytes. Biorheology 53(5-6): 237-249

Hui, L.; Hui, L.; Tong, H. 2016: Prediction of the Long-term Efficacy of STA-MCA Bypass by DSC-Pi. Translational Neuroscience 7(1): 110-115

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Zheng, S.; Xiao, M.; Tian, Y.; Chen, X. 2017: Prediction of the lowest charge-transfer excited-state energy at the donor-acceptor interface in a condensed phase using ground-state DFT calculations with generalized Kohn-Sham functionals. Journal of Molecular Modeling 23(8): 235

García-Ramos, A.; Torrejón, A.; Feriche, B.én.; Morales-Artacho, A.J.; Pérez-Castilla, A.; Padial, P.; Haff, G.G. 2018: Prediction of the Maximum Number of Repetitions and Repetitions in Reserve from Barbell Velocity. International Journal of Sports Physiology and Performance 13(3): 353-359

Rioland, G.; Dutournié, P.; Faye, D.; Daou, T.J.; Patarin, J.ël. 2016: Prediction of the mechanical properties of zeolite pellets for aerospace molecular decontamination applications. Beilstein Journal of Nanotechnology 7: 1761-1771

Jang, Y.-E.; Kim, E.-H.; Song, I.-K.; Lee, J.-H.; Ryu, H.-G.; Kim, H.-S.; Kim, J.-T. 2017: Prediction of the mid-tracheal level using surface anatomical landmarks in adults: Clinical implication of endotracheal tube insertion depth. Medicine 96(12): E6319

Ginzburg, I. 2017: Prediction of the moments in advection-diffusion lattice Boltzmann method. II. Attenuation of the boundary layers via double-Λ bounce-back flux scheme. Physical Review e 95(1-1): 013305

Ginzburg, I. 2017: Prediction of the moments in advection-diffusion lattice Boltzmann method. I. Truncation dispersion, skewness, and kurtosis. Physical Review e 95(1-1): 013304

Chin, J.-H.; Lee, E.-H.; Kim, J.-I.; Choi, I.-C. 2017: Prediction of the optimal depth for superior vena cava cannulae with cardiac computed tomography during minimally invasive cardiac surgery: a prospective observational cohort study. Bmc Anesthesiology 17(1): 56

Moshirvaziri, H.; Ramezan-Arab, N.; Asgari, S. 2016: Prediction of the outcome in cardiac arrest patients undergoing hypothermia using EEG wavelet entropy. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2016: 3777-3780

Lee, D.Gyu.; Kwak, S.Gyu.; Chang, M.Cheol. 2017: Prediction of the outcome of bladder dysfunction based on electrically induced reflex findings in patients with cauda equina syndrome: A retrospective study. Medicine 96(21): E7014

Sylvestre, A.; Desmarais, C.; Meyer, Fçois.; Bairati, I.; Leblond, J. 2018: Prediction of the outcome of children who had a language delay at age 2 when they are aged 4: Still a challenge. International Journal of Speech-Language Pathology 20(7): 731-744

Fudalej, P.; Dragan, M.; Wedrychowska-Szulc, B. 2011: Prediction of the outcome of orthodontic treatment of Class IIi malocclusions--a systematic review. European Journal of Orthodontics 33(2): 190-197

Lin, L.; Jin, L.; Wang, Z.-H.; Cui, Z.-J.; Ma, Y. 2017: Prediction of the potential distribution of Tibetan medicinal Lycium ruthenicum in context of climate change. Zhongguo Zhong Yao Za Zhi 42(14): 2659-2669

Ito, K.; Kobayashi, K. 2017: Prediction of the potential risk of idiosyncratic drug toxicity. Drug Metabolism and Pharmacokinetics 32(1): 1

Poltaretskyi, S.; Chaoui, J.; Mayya, M.; Hamitouche, C.; Bercik, M.J.; Boileau, P.; Walch, G. 2017: Prediction of the pre-morbid 3D anatomy of the proximal humerus based on statistical shape modelling. Bone and Joint Journal 99-B(7): 927-933

Yabuuchi, H.; Kawanami, S.; Iwama, E.; Okamoto, I.; Kamitani, T.; Sagiyama, K.; Yamasaki, Y.; Honda, H. 2018: Prediction of Therapeutic Effect of Chemotherapy for NSCLC Using Dual-Input Perfusion CT Analysis: Comparison among Bevacizumab Treatment, Two-Agent Platinum-based Therapy without Bevacizumab, and other Non-Bevacizumab Treatment Groups. Radiology 286(2): 685-695

Liang, G.; DeYonker, N.J.; Zhao, X.; Webster, C.E. 2017: Prediction of the reduction potential in transition-metal containing complexes: how expensive? for what accuracy?. Journal of Computational Chemistry 38(28): 2430-2438

Vandenplas, J.ér.ém.; Windig, J.J.; Calus, M.P.L. 2017: Prediction of the reliability of genomic breeding values for crossbred performance. Genetics Selection Evolution: Gse 49(1): 43

Alassaf, N. 2018: Prediction of the requirement of open reduction for developmental dysplasia of the hip. Journal of International Medical Research 46(1): 54-61

Khan, W.S.; Hamadneh, N.N.; Khan, W.A. 2017: Prediction of thermal conductivity of polyvinylpyrrolidone (PVP) electrospun nanocomposite fibers using artificial neural network and prey-predator algorithm. Plos one 12(9): E0183920

Wang, D-Hui.; Zhou, H-Ying.; Hu, C-Hao.; Zhong, Y.; Oganov, A.R.; Rao, G-Hui. 2017: Prediction of thermodynamically stable Li-B compounds at ambient pressure. Physical Chemistry Chemical Physics: Pccp 19(12): 8471-8477

Ahn, S.; Jo, S.; Jun, S.Beom.; Lee, H.Woon.; Lee, S. 2017: Prediction of the Seizure Suppression Effect by Electrical Stimulation via a Computational Modeling Approach. Frontiers in Computational Neuroscience 11: 39

Liu, W.-T.; Wu, H.-T.; Juang, J.-N.; Wisniewski, A.; Lee, H.-C.; Wu, D.; Lo, Y.-L. 2017: Prediction of the severity of obstructive sleep apnea by anthropometric features via support vector machine. Plos one 12(5): E0176991

Allard, M.-A.; Baillié, G.ël.; Castro-Benitez, C.; Faron, M.; Blandin, F.éd.ér.; Cherqui, D.; Castaing, D.; Cunha, A.S.; Adam, R.é; Vibert, Ér. 2017: Prediction of the Total Liver Weight using anthropological clinical parameters: does complexity result in better accuracy?. Hpb: the Official Journal of the International Hepato Pancreato Biliary Association 19(4): 338-344

Ellens, H.; Johnson, M.; Lawrence, S.K.; Watson, C.; Chen, L.; Richards-Peterson, L.E. 2017: Prediction of the Transporter-Mediated Drug-Drug Interaction Potential of Dabrafenib and its Major Circulating Metabolites. Drug Metabolism and Disposition: the Biological Fate of Chemicals 45(6): 646-656

Norrby, S.; Bergman, R.; Hirnschall, N.; Nishi, Y.; Findl, O. 2017: Prediction of the true IOL position. British Journal of Ophthalmology 101(10): 1440-1446

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Bhowmik, R.; Berry, R.J.; Durstock, M.F.; Leever, B.J. 2017: Prediction of the Wetting Behavior of Active and Hole-Transport Layers for Printed Flexible Electronic Devices Using Molecular Dynamics Simulations. Acs Applied Materials and Interfaces 9(22): 19269-19277

Zhao, K.; Zhou, X-Dong.; Liu, X-Qiang.; Lu, L.; Wu, Z-Bo.; Peng, F.; Ju, X-Yu.; Yang, L-Zhong. 2016: Prediction of Three-Dimensional Downward Flame Spread Characteristics over Poly(methyl methacrylate) Slabs in Different Pressure Environments. Materials 9(11)

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Hai, J-Jo.; Chan, P-Hei.; Chan, Y-Hang.; Fong, C-Ho-Yi.; Huang, D.; Li, W-Hua.; Yin, L-Xue.; Lau, C-Pak.; Tse, H-Fat.; Siu, C-Wah. 2016: Prediction of Thromboembolic Events in Heart Failure Patients in Sinus Rhythm: The Hong Kong Heart Failure Registry. Plos one 11(12): E0169095

Wang, T.; Kang, X.; He, L.; Liu, Z.; Xu, H.; Zhao, A. 2017: Prediction of thrombophilia in patients with unexplained recurrent pregnancy loss using a statistical model. International Journal of Gynaecology and Obstetrics: the Official Organ of the International Federation of Gynaecology and Obstetrics 138(3): 283-287

Hosseinzadegan, H.; Tafti, D.K. 2017: Prediction of Thrombus Growth: Effect of Stenosis and Reynolds Number. Cardiovascular Engineering and Technology 8(2): 164-181

Zhang, R.; Zhang, G.; Wang, R.; Tan, J.; He, Y.; Meng, Z. 2017: Prediction of thyroidal 131i effective half-life in patients with Graves' disease. Oncotarget 8(46): 80934-80940

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Miyoshi, Y.; Yoneyama, S.; Kawahara, T.; Hattori, Y.; Teranishi, J.-I.; Ohta, J.-I.; Takebayashi, S.; Yokomizo, Y.; Hayashi, N.; Uemura, H. 2017: Prediction of time to Castration-Resistant Prostate Cancer Using Bone Scan Index in Men with Metastatic Hormone-Sensitive Prostate Cancer. Urologia Internationalis 99(4): 400-405

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Nigade, P.B.; Gundu, J.; Sreedhara Pai, K.; Nemmani, K.V.S. 2017: Prediction of Tissue-to-Plasma Ratios of Basic Compounds in Mice. European Journal of Drug Metabolism and Pharmacokinetics 42(5): 835-847

Jia, Y.-Z.; Ji, W.-X.; Zhang, C.-W.; Li, P.; Zhang, S.-F.; Wang, P.-J.; Li, S.-S.; Yan, S.-S. 2017: Prediction of topological crystalline insulators and topological phase transitions in two-dimensional PbTe films. Physical Chemistry Chemical Physics: Pccp 19(43): 29647-29652

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Damasceno, Év.P.; de Figuerêdo, L.ív.P.; Pimentel, M.íl.F.; Loureiro, S.; Costa-Lotufo, L.íc.V. 2017: Prediction of toxicity of zinc and nickel mixtures to Artemia sp. at various salinities: from additivity to antagonism. Ecotoxicology and Environmental Safety 142: 322-329

Briones-Orta, M.A.; Avendaño-Vázquez, S.E.én.; Ivette Aparicio-Bautista, D.; Coombes, J.D.; Weber, G.F.; Syn, W.-K. 2017: Prediction of transcription factor bindings sites affected by SNPs located at the osteopontin promoter. Data in Brief 14: 538-542

Studerus, E.; Ramyead, A.; Riecher-Rössler, A. 2017: Prediction of transition to psychosis in patients with a clinical high risk for psychosis: a systematic review of methodology and reporting. Psychological Medicine 47(7): 1163-1178

Posada, M.M.; Cannady, E.A.; Payne, C.D.; Zhang, X.; Bacon, J.A.; Pak, Y.A.; Higgins, J.W.; Shahri, N.; Hall, S.D.; Hillgren, K.M. 2017: Prediction of Transporter-Mediated Drug-Drug Interactions for Baricitinib. Clinical and Translational Science 10(6): 509-519

Shiozawa, S.; Usui, T.; Kuhara, K.; Tsuchiya, A.; Miyauchi, T.; Kono, T.; Asaka, S.; Yamaguchi, K.; Yokomizo, H.; Shimakawa, T.; Yoshimatsu, K.; Katsube, T.; Naritaka, Y. 2016: Prediction of Treatment Effect of Transcatheter Arterial Chemoembolization for Hepatocellular Carcinoma Using Computed Tomography(CT)-Attenuation Value. Gan to Kagaku Ryoho. Cancer and ChemoTherapy 43(12): 1487-1489

Rethorst, C.D.; South, C.C.; Rush, A.J.; Greer, T.L.; Trivedi, M.H. 2017: Prediction of treatment outcomes to exercise in patients with nonremitted major depressive disorder. Depression and Anxiety 34(12): 1116-1122

Çakıroğlu, Y.ği.; Doğer, E.; Yıldırım Kopuk, Şu.; Özcan, C.; Nalbant, B.ül.; Çorakçı, A.ın.; Yücesoy, İz. 2014: Prediction of tumor grade and stage in endometrial carcinoma by preoperative assessment of sonographic endometrial thickness: Is it possible?. Turkish Journal of Obstetrics and Gynecology 11(4): 211-214

Cui, Z.-H.; Jimenez-Izal, E.; Alexandrova, A.N. 2017: Prediction of Two-Dimensional Phase of Boron with Anisotropic Electric Conductivity. Journal of Physical Chemistry Letters 8(6): 1224-1228

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Leong, A.; Daya, N.; Porneala, B.; Devlin, J.J.; Shiffman, D.; McPhaul, M.J.; Selvin, E.; Meigs, J.B. 2018: Prediction of Type 2 Diabetes by Hemoglobin A 1c in Two Community-Based Cohorts. Diabetes Care 41(1): 60-68

Vieira, M.C.; White, S.L.; Patel, N.; Seed, P.T.; Briley, A.L.; Sandall, J.; Welsh, P.; Sattar, N.; Nelson, S.M.; Lawlor, D.A.; Poston, L.; Pasupathy, D.; Poston, L.; Shennan, A.; Briley, A.; Singh, C.; Seed, P.; Sandall, J.; Sanders, T.; Patel, N.; Flynn, A.; Badger, S.; Barr, S.; Holmes, B.; Goff, L.; Hunt, C.; Filmer, J.; Fetherstone, J.; Scholtz, L.; Tarft, H.; Lucas, A.; Tekletdadik, T.; Ricketts, D.; Gill, C.; Ignatian, A.S.; Boylen, C.; Adegoke, F.; Lawley, E.; Butler, J.; Maitland, R.; Vieira, M.; Pasupathy, D.; Oteng-Ntim, E.; Khazaezadeh, N.; Demilew, J.; O'Connor, S.; Evans, Y.; O'Donnell, S.; de la Llera, A.; Gutzwiller, G.; Hagg, L.; Robson, S.; Bell, R.; Hayes, L.; Kinnunen, T.; McParlin, C.; Miller, N.; Kimber, A.; 2017: Prediction of uncomplicated pregnancies in obese women: a prospective multicentre study. Bmc Medicine 15(1): 194

André, E.; Lufungulo Bahati, Y.; Mulume Musafiri, E.; Bahati Rusumba, O.; Van der Linden, D.; Zech, F. 2017: Prediction of Under-Detection of Paediatric Tuberculosis in the Democratic Republic of Congo: Experience of Six Years in the South-Kivu Province. Plos one 12(1): E0169014

Bryk, A.H.; Plens, K.; Undas, A. 2017: Prediction of unstable anticoagulation with acenocoumarol versus warfarin in atrial fibrillation. Cardiology Journal 24(5): 477-483

Erdogan, A.; Argall, B.D. 2017: Prediction of user preference over shared-control paradigms for a robotic wheelchair. IEEE .. International Conference on Rehabilitation Robotics: 2017: 1106-1111

Rashid, M.I.; Naz, A.; Ali, A.; Andleeb, S. 2017: Prediction of vaccine candidates against Pseudomonas aeruginosa: An integrated genomics and proteomics approach. Genomics 109(3-4): 274-283

Mizrachi, Y.; Barber, E.; Kovo, M.; Bar, J.; Lurie, S. 2018: Prediction of vaginal birth after one ceasarean delivery for non-progressive labor. Archives of Gynecology and Obstetrics 297(1): 85-91

van Vuuren, T.Maj.; Van Zandvoort, C.; Doganci, S.; Zwiers, I.; tenCate-Hoek, A.J.; Kurstjens, R.Lm.; Wittens, C.Ha. 2017: Prediction of venous wound healing with laser speckle imaging. Phlebology 32(10): 658-664

Wolf, A.; Fanshawe, T.R.; Sariaslan, A.; Cornish, R.; Larsson, H.; Fazel, S. 2018: Prediction of violent crime on discharge from secure psychiatric hospitals: a clinical prediction rule (FoVOx). European Psychiatry: the Journal of the Association of European Psychiatrists 47: 88-93

Zhang, M.; Yang, L.; Ren, J.; Ahlgren, N.A.; Fuhrman, J.A.; Sun, F. 2017: Prediction of virus-host infectious association by supervised learning methods. Bmc Bioinformatics 18(Suppl. 3): 60

Becerra, A.és.; Bucheli, V.A.; Moreno, P.A. 2017: Prediction of virus-host protein-protein interactions mediated by short linear motifs. Bmc Bioinformatics 18(1): 163

Cairns, A.J.; Kavanagh, D.J.; Dark, F.; McPhail, S.M. 2017: Prediction of vocational participation and global role functioning in help-seeking young adults, from neurocognitive, demographic and clinical variables. Journal of Affective Disorders 221: 158-164

Wu, M.-J.; Mwangi, B.; Passos, I.C.; Bauer, I.E.; Cao, B.; Frazier, T.W.; Zunta-Soares, G.B.; Soares, J.C. 2017: Prediction of vulnerability to bipolar disorder using multivariate neurocognitive patterns: a pilot study. International Journal of Bipolar Disorders 5(1): 32

Jasseron, C.; Legeai, C.; Jacquelinet, C.; Leprince, P.; Cantrelle, C.; Audry, B.ît.; Porcher, R.; Bastien, O.; Dorent, R. 2017: Prediction of Waitlist Mortality in Adult Heart Transplant Candidates: the Candidate Risk Score. Transplantation 101(9): 2175-2182

Hansen, E.A.; Nielsen, A.M.øl.; Kristensen, L.A.R.; Madeleine, P.; Voigt, M. 2018: Prediction of walk-to-run transition using stride frequency: a test-retest reliability study. Gait and Posture 60: 71-75

Swainson, M.G.; Batterham, A.M.; Tsakirides, C.; Rutherford, Z.H.; Hind, K. 2017: Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables. Plos one 12(5): E0177175

Weigel, K.A.; Pralle, R.S.; Adams, H.; Cho, K.; Do, C.; White, H.M. 2017: Prediction of whole-genome risk for selection and management of hyperketonemia in Holstein dairy cattle. Journal of Animal Breeding and Genetics 134(3): 275-285

De Koning, M.E.; Scheenen, M.E.; van der Horn, H.J.; Timmerman, M.E.; Hageman, G.; Roks, G.; Spikman, J.M.; van der Naalt, J. 2017: Prediction of work resumption and sustainability up to 1 year after mild traumatic brain injury. Neurology 89(18): 1908-1914

Soewondo, P.; Suyono, S.; Sastrosuwignyo, M.K.; Harahap, A.R.; Sutrisna, B.; Makmun, L.H. 2017: Prediction of Wound Healing in Diabetic Foot Ulcers: an Observational Study in Tertiary Hospital in Indonesia. Acta Medica Indonesiana 49(1): 41-51

Yu, X.; Hou, H.; Wang, B. 2017: Prediction on dielectric strength and boiling point of gaseous molecules for replacement of SF6. Journal of Computational Chemistry 38(10): 721-729

Zhao, J.; Liu, C.; Guo, W.; Ma, J. 2017: Prediction on the light-assisted exfoliation of multilayered arsenene by the photo-isomerization of azobenzene. Nanoscale 9(21): 7006-7011

Kim, S.; Baladandayuthapani, V.; Lee, J.Jack. 2017: Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression. Statistics in Biosciences 9(1): 217-245

Nguimdo, R.Modeste.; Lacot, E.; Jacquin, O.; Hugon, O.; Van der Sande, G.; Guillet de Chatellus, H. 2017: Prediction performance of reservoir computing systems based on a diode-pumped erbium-doped microchip laser subject to optical feedback. Optics Letters 42(3): 375-378

Bašová, P.; Pešta, M.; Sochor, M.; Stopka, T.áš 2017: Prediction Potential of Serum miR-155 and miR-24 for Relapsing Early Breast Cancer. International Journal of Molecular Sciences 18(10)

Shuang Li; Shiji Song; Gao Huang 2017: Prediction Reweighting for Domain Adaptation. IEEE Transactions on Neural Networks and Learning Systems 28(7): 1682-1695

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Volpicelli, G.; Vanni, S.; Becattini, C.; Sferrazza Papa, G.Francesco.; Gigli, C.; Grifoni, S.; Nazerian, P. 2017: Prediction Rule for Diagnosis of Pulmonary Embolism Enhanced by Lung and Venous Ultrasound: Making Confusion or Increasing Efficiency?. Academic emergency medicine: official journal of the Society for Academic Emergency Medicine 24(4): 498-499

Vukmirović, M.; Bošković, A.; Tomašević Vukmirović, I.; Vujadinovic, R.; Fatić, N.; Bukumirić, Z.; Vukmirović, F. 2017: Predictions and Outcomes of Atrial Fibrillation in the Patients with Acute Myocardial Infarction. Open Medicine 12: 115-124

Miyares, M.A. 2016: Predictions and presumptive treatment of heparin-induced thrombocytopenia. American Journal of Health-System Pharmacy: Ajhp: Official Journal of the American Society of Health-System Pharmacists 73(10): 612-614

Darmon, M.; Ostermann, M.; Joannidis, M. 2017: Predictions are difficult…especially about AKi. Intensive Care Medicine 43(6): 932-934

Lin, K.J.; Singer, D.E.; Glynn, R.J.; Blackley, S.; Zhou, L.; Liu, J.; Dube, G.; Oertel, L.B.; Schneeweiss, S. 2017: Prediction Score for Anticoagulation Control Quality Among Older Adults. Journal of the American Heart Association 6(10)

Rogers, J.R.; McHugh, S.M.; Lin, Y.-S. 2017: Predictions for α-Helical Glycopeptide Design from Structural Bioinformatics Analysis. Journal of Chemical Information and Modeling 57(10): 2598-2611

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Teramoto, M.; Cross, C.L.; Rieger, R.H.; Maak, T.G.; Willick, S.E. 2018: Predictive Validity of National Basketball Association Draft Combine on Future Performance. Journal of Strength and Conditioning Research 32(2): 396-408