Toxic substances in blood: an analysis of current recommendations under a Bayesian (decision) approach
Taroni, F.; Biedermann, A.; Bozza, S.; Vuille, J.; Augsburger, M.
Law Probability and Risk 13(1): 27-45
2014
ISSN/ISBN: 1470-8396 DOI: 10.1093/lpr/mgt012
Accession: 064598709
Full Text Article emailed within 0-6 h: $19.90
Related References
Derosa, C.T. 1995: Decision support methodologies for human health assessment of toxic substances: Agency for toxic substances and disease registry's perspectives on collaboration and infrastructure development among government, academia, and industry Toxicology Letters 79(1-3): 283-285Derosa, C.T. 1995: Decision support methodologies for human health assessment of toxic substances : Agency for Toxic Substances and Disease Registry's perspectives on collaboration and infrastructure development among government, academia, and industry Toxicol. Lett 79(1-3): 283-285
Shibayama, K.; Ebihara, K.; Shinozaki, T.; Shida, K. 1973: Studies on toxic substances in the uremic blood. I. Effects of toxic substances in the uremic blood on PAH uptake and ATP-ase activity of rabbit renal cortex Nihon Jinzo Gakkai Shi 15(1): 33-34
Kodaira, Y. 1960: Studies on the toxic substances produced by museardine fung. III. Existence of the toxic substances in the blood of silkworms attacked by various muscardine fungi Res Rept Fac Textile And Sericult Shinshu Univ 10: 130-134
Hayashi, T.I.; Kashiwagi, N. 2011: A Bayesian approach to probabilistic ecological risk assessment: risk comparison of nine toxic substances in Tokyo surface waters Environmental Science and Pollution Research International 18(3): 365-375
Natanegara, F.; Neuenschwander, B.; Seaman, J.W.; Kinnersley, N.; Heilmann, C.R.; Ohlssen, D.; Rochester, G. 2014: The current state of Bayesian methods in medical product development: survey results and recommendations from the DIA Bayesian Scientific Working Group Pharmaceutical Statistics 13(1): 3-12
Faya, P.; Sondag, P.; Novick, S.; Banton, D.; Seaman, J.W.; Stamey, J.D.; Boulanger, B. 2021: The current state of Bayesian methods in nonclinical pharmaceutical statistics: Survey results and recommendations from the DIA/ASA-BIOP Nonclinical Bayesian Working Group Pharmaceutical Statistics 20(2): 245-255
Marhamati, N.; Buxton, E.K.; Rahimi, S. 2018: Integration of Z-numbers and Bayesian decision theory: a hybrid approach to decision making under uncertainty and imprecision Applied Soft Computing 72: 273-290
Tsukioka, M. 1959: Experimental approach through BSP retention test to the toxic liver-injuries due to P. islandicum Sopp growing rice, fungus mat and toxic substances Folia Pharmacologica Japonica 55(6): 1367-1389
Ling, C.H.E.N.; Jun, S.H.A.O. 2000: A Bayesian decision rule for remediation actions at toxic waste sites Statistics and Probability Letters 50(1): 83-88
Scheiber, C. 1975: Wood species that endanger health: toxic substances, diseases and recommendations for hygiene and work safety Holzindustrie 28(8; 9): 245-247; 279-283
Camara, V.A.R. 2009: A new Approximate Bayesian Approach for Decision Making about the Variance of a Gaussian Distribution Versus the Classical Approach Journal of Modern Applied Statistical Methods 8(1): 237-252
Mégarbane, B.; Borron, S.W.; Baud, Fédéric.J. 2005: Current recommendations for treatment of severe toxic alcohol poisonings Intensive Care Medicine 31(2): 189-195
Ocker, H.D. 1983: Toxic substances in cereals--current state of knowledge Getreide Mehl und Brot 37(1): 3-7
Wang, C.; Zhu, H.; Wang, P.; Zhu, C.; Zhang, X.; Chen, E.; Xiong, H. 2022: Personalized and Explainable Employee Training Course Recommendations: a Bayesian Variational Approach ACM Transactions on Information Systems 40(4): 1-32
Dehnad, K. 1990: Decision Analysis: a Bayesian Approach Technometrics 32(2): 232-233
Lavrov, V.I.; Goncharov, I.B.; Davydkin, A.F.; Romanov, A.N.; Ivchenko, V.F. 1986: Test à la paramécie pour substances toxiques dans le sang des hommes en apesanteur simulée - The paramecin test for toxic substances in blood of men exposed to simulated weightlessness Kosmiceskaa Biologia i Aviakosmiceskaa Medicina 20(2): 58-60
Shiran, M.B.; Barzegar Marvasti, M.; Shakeri-Zadeh, A.; Shahidi, M.; Tabkhi, N.; Farkhondeh, F.; Kalantar, E.; Asadinejad, A. 2017: Enhancement of Toxic Substances Clearance from Blood Equvalent Solution and Human Whole Blood through High Flux Dialyzer by 1 MHz Ultrasound Journal of Biomedical Physics and Engineering 7(2): 107-116
Niedzinski, C.; Morawski, R. 2000: Bayesian approach to spectrophotometric analysis of multicomponent substances IEEE Transactions on Instrumentation and Measurement 49(3): 637-642
Kant, V.; Bharadwaj, K.K. 2013: Integrating Collaborative and Reclusive Methods for Effective Recommendations: A Fuzzy Bayesian Approach International Journal of Intelligent Systems 28(11): 1099-1123