 Markov Chains
"Markov Chains" 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 stochastic process such that the conditional probability distribution for a state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system.
| Descriptor ID |
D008390
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| MeSH Number(s) |
E05.318.740.600.500 E05.318.740.996.500 G17.830.500 N05.715.360.750.625.500 N05.715.360.750.770.500 N06.850.520.830.600.500 N06.850.520.830.996.500
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| Concept/Terms |
Markov Chains- Markov Chains
- Chains, Markov
- Markov Process
- Markov Processes
- Process, Markov
- Processes, Markov
- Markov Chain
- Chain, Markov
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Below are MeSH descriptors whose meaning is more general than "Markov Chains".
Below are MeSH descriptors whose meaning is more specific than "Markov Chains".
This graph shows the total number of publications written about "Markov Chains" by people in this website by year, and whether "Markov Chains" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 1994 | 0 | 1 | 1 | | 2001 | 0 | 1 | 1 | | 2005 | 0 | 1 | 1 | | 2006 | 0 | 1 | 1 | | 2007 | 1 | 0 | 1 | | 2008 | 1 | 2 | 3 | | 2010 | 0 | 1 | 1 | | 2011 | 0 | 1 | 1 | | 2012 | 0 | 1 | 1 | | 2013 | 0 | 2 | 2 | | 2014 | 0 | 2 | 2 | | 2015 | 0 | 1 | 1 | | 2017 | 0 | 4 | 4 | | 2018 | 0 | 1 | 1 | | 2019 | 1 | 0 | 1 | | 2020 | 0 | 3 | 3 |
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Below are the most recent publications written about "Markov Chains" by people in Profiles.
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Bashir NS, Walters TD, Griffiths AM, Ito S, Ungar WJ. Cost-effectiveness and Clinical Outcomes of Early Anti-Tumor Necrosis Factor-a Intervention in Pediatric Crohn's Disease. Inflamm Bowel Dis. 2020 07 17; 26(8):1239-1250.
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Anderson BR, Gotlieb EG, Hill K, McHugh KE, Scheurer MA, Mery CM, Pelletier GJ, Kaltman JR, White OJ, Trachtenberg FL, Hollenbeck-Pringle D, McCrindle BW, Sylvester DM, Eckhauser AW, Pasquali SK, Anderson JB, Schamberger MS, Shashidharan S, Jacobs JP, Jacobs ML, Boskovski M, Newburger JW, Nathan M. Registry-based trials: a potential model for cost savings? Cardiol Young. 2020 Jun; 30(6):807-817.
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Liu K, Saarela O, Feldman BM, Pullenayegum E. Estimation of causal effects with repeatedly measured outcomes in a Bayesian framework. Stat Methods Med Res. 2020 09; 29(9):2507-2519.
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Tak CR, Biltaji E, Kohlmann W, Maese L, Hainaut P, Villani A, Malkin D, Sherwin CMT, Brixner DI, Schiffman JD. Cost-effectiveness of early cancer surveillance for patients with Li-Fraumeni syndrome. Pediatr Blood Cancer. 2019 05; 66(5):e27629.
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Vidaurre D, Hunt LT, Quinn AJ, Hunt BAE, Brookes MJ, Nobre AC, Woolrich MW. Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks. Nat Commun. 2018 07 30; 9(1):2987.
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Krijkamp EM, Alarid-Escudero F, Enns EA, Jalal HJ, Hunink MGM, Pechlivanoglou P. Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial. Med Decis Making. 2018 04; 38(3):400-422.
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Hollman C, Paulden M, Pechlivanoglou P, McCabe C. A Comparison of Four Software Programs for Implementing Decision Analytic Cost-Effectiveness Models. Pharmacoeconomics. 2017 Aug; 35(8):817-830.
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Zhang J, Khan A, Kennard A, Grigg ME, Parkinson J. PopNet: A Markov Clustering Approach to Study Population Genetic Structure. Mol Biol Evol. 2017 07 01; 34(7):1799-1811.
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Simpson JT, Workman RE, Zuzarte PC, David M, Dursi LJ, Timp W. Detecting DNA cytosine methylation using nanopore sequencing. Nat Methods. 2017 Apr; 14(4):407-410.
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Xu L, Paterson AD, Xu W. Bayesian latent variable models for hierarchical clustered count outcomes with repeated measures in microbiome studies. Genet Epidemiol. 2017 Apr; 41(3):221-232.
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