Bayes Theorem
"Bayes Theorem" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihoods of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.
Descriptor ID |
D001499
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MeSH Number(s) |
E05.318.740.600.200 N05.715.360.750.625.150 N06.850.520.830.600.200
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Concept/Terms |
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Below are MeSH descriptors whose meaning is more general than "Bayes Theorem".
Below are MeSH descriptors whose meaning is more specific than "Bayes Theorem".
This graph shows the total number of publications written about "Bayes Theorem" by people in this website by year, and whether "Bayes Theorem" was a major or minor topic of these publications.
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Year | Major Topic | Minor Topic | Total |
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2009 | 0 | 1 | 1 | 2010 | 0 | 3 | 3 | 2011 | 0 | 1 | 1 | 2012 | 1 | 0 | 1 | 2013 | 0 | 2 | 2 | 2014 | 0 | 1 | 1 | 2015 | 0 | 3 | 3 | 2016 | 0 | 1 | 1 | 2017 | 0 | 1 | 1 | 2018 | 1 | 1 | 2 | 2019 | 1 | 1 | 2 | 2020 | 1 | 6 | 7 | 2021 | 0 | 3 | 3 |
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Below are the most recent publications written about "Bayes Theorem" by people in Profiles.
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Wadon ME, Bailey GA, Yilmaz Z, Hubbard E, AlSaeed M, Robinson A, McLauchlan D, Barbano RL, Marsh L, Factor SA, Fox SH, Adler CH, Rodriguez RL, Comella CL, Reich SG, Severt WL, Goetz CG, Perlmutter JS, Jinnah HA, Harding KE, Sandor C, Peall KJ. Non-motor phenotypic subgroups in adult-onset idiopathic, isolated, focal cervical dystonia. Brain Behav. 2021 08; 11(8):e2292.
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Petyuk VA, Yu L, Olson HM, Yu F, Clair G, Qian WJ, Shulman JM, Bennett DA. Proteomic Profiling of the Substantia Nigra to Identify Determinants of Lewy Body Pathology and Dopaminergic Neuronal Loss. J Proteome Res. 2021 05 07; 20(5):2266-2282.
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Liotta EM, Batra A, Koralnik IJ. Reply to COVID-19 encephalopathy, Bayes rule, and a plea for case-control studies. Ann Clin Transl Neurol. 2021 03; 8(3):726.
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Forsythe B, Lavoie-Gagne O, Patel BH, Lu Y, Ritz E, Chahla J, Okoroha KR, Allen AA, Nwachukwu BU. Efficacy of Arthroscopic Surgery in the Management of Adhesive Capsulitis: A Systematic Review and Network Meta-analysis of Randomized Controlled Trials. Arthroscopy. 2021 07; 37(7):2281-2297.
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Puduvalli VK, Wu J, Yuan Y, Armstrong TS, Vera E, Wu J, Xu J, Giglio P, Colman H, Walbert T, Raizer J, Groves MD, Tran D, Iwamoto F, Avgeropoulos N, Paleologos N, Fink K, Peereboom D, Chamberlain M, Merrell R, Penas Prado M, Yung WKA, Gilbert MR. A Bayesian adaptive randomized phase II multicenter trial of bevacizumab with or without vorinostat in adults with recurrent glioblastoma. Neuro Oncol. 2020 10 14; 22(10):1505-1515.
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Luningham JM, Chen J, Tang S, De Jager PL, Bennett DA, Buchman AS, Yang J. Bayesian Genome-wide TWAS Method to Leverage both cis- and trans-eQTL Information through Summary Statistics. Am J Hum Genet. 2020 10 01; 107(4):714-726.
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Benedetto U, Dimagli A, Sinha S, Cocomello L, Gibbison B, Caputo M, Gaunt T, Lyon M, Holmes C, Angelini GD. Machine learning improves mortality risk prediction after cardiac surgery: Systematic review and meta-analysis. J Thorac Cardiovasc Surg. 2022 06; 163(6):2075-2087.e9.
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Izci Balserak B, Pien GW, Prasad B, Mastrogiannis D, Park C, Quinn LT, Herdegen J, Carley DW. Obstructive Sleep Apnea Is Associated with Newly Diagnosed Gestational Diabetes Mellitus. Ann Am Thorac Soc. 2020 06; 17(6):754-761.
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Klein HU, Schäfer M, Bennett DA, Schwender H, De Jager PL. Bayesian integrative analysis of epigenomic and transcriptomic data identifies Alzheimer's disease candidate genes and networks. PLoS Comput Biol. 2020 04; 16(4):e1007771.
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Fogg L, Swanson B. Three Types of Falsehoods: Lies, Damned Lies, and Non-Bayesian Statistics. J Assoc Nurses AIDS Care. 2020 Jan-Feb; 31(1):1-2.
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