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Items: 1 to 20 of 102

1.

Markov models in medical decision making: a practical guide.

Sonnenberg FA, Beck JR.

Med Decis Making. 1993 Oct-Dec;13(4):322-38.

PMID:
8246705
2.

[Decision analysis in radiology using Markov models].

Golder W.

Rofo. 2000 Jan;172(1):80-5. German.

PMID:
10719468
3.

Use of Markov series and Monte Carlo simulation in predicting replacement valve performances.

de Kruyk AR, van der Meulen JH, van Herwerden LA, Bekkers JA, Steyerberg EW, Dekker R, Habbema JD.

J Heart Valve Dis. 1998 Jan;7(1):4-12.

PMID:
9502132
4.

The Markov process in medical prognosis.

Beck JR, Pauker SG.

Med Decis Making. 1983;3(4):419-458.

PMID:
6668990
5.
6.

Data-driven Markov models and their application in the evaluation of adverse events in radiotherapy.

Abler D, Kanellopoulos V, Davies J, Dosanjh M, Jena R, Kirkby N, Peach K.

J Radiat Res. 2013 Jul;54 Suppl 1:i49-55. doi: 10.1093/jrr/rrt040.

7.

A piecewise-homogeneous Markov chain process of lung transplantation.

Sharples LD, Taylor GI, Faddy M.

J Epidemiol Biostat. 2001;6(4):349-55.

PMID:
12036269
8.

Mathematical models in decision analysis.

Tom E, Schulman KA.

Infect Control Hosp Epidemiol. 1997 Jan;18(1):65-73. Review.

PMID:
9013249
9.
10.

Correlations in uncertainty analysis for medical decision making: an application to heart-valve replacement.

Chessa AG, Dekker R, van Vliet B, Steyerberg EW, Habbema JD.

Med Decis Making. 1999 Jul-Sep;19(3):276-86.

PMID:
10424834
11.

A mathematical approach for evaluating Markov models in continuous time without discrete-event simulation.

van Rosmalen J, Toy M, O'Mahony JF.

Med Decis Making. 2013 Aug;33(6):767-79. doi: 10.1177/0272989X13487947.

PMID:
23715464
12.

Scalable approximate policies for Markov decision process models of hospital elective admissions.

Zhu G, Lizotte D, Hoey J.

Artif Intell Med. 2014 May;61(1):21-34. doi: 10.1016/j.artmed.2014.04.001.

PMID:
24791675
13.

Probabilistic analysis of decision trees using Monte Carlo simulation.

Critchfield GC, Willard KE.

Med Decis Making. 1986 Apr-Jun;6(2):85-92.

PMID:
3702625
14.
15.

Graphical representation of life paths to better convey results of decision models to patients.

Rubrichi S, Rognoni C, Sacchi L, Parimbelli E, Napolitano C, Mazzanti A, Quaglini S.

Med Decis Making. 2015 Apr;35(3):398-402. doi: 10.1177/0272989X14565822.

PMID:
25589524
16.

Choosing the order of deceased donor and living donor kidney transplantation in pediatric recipients: a Markov decision process model.

Van Arendonk KJ, Chow EK, James NT, Orandi BJ, Ellison TA, Smith JM, Colombani PM, Segev AD.

Transplantation. 2015 Feb;99(2):360-6. doi: 10.1097/TP.0000000000000588.

17.

Results of aortic valve replacement.

Nicks R, Jairaj PS.

Med J Aust. 1973 Jan 13;1(2):63-5. No abstract available.

PMID:
4758160
18.

Uncertainty and patient heterogeneity in medical decision models.

Groot Koerkamp B, Weinstein MC, Stijnen T, Heijenbrok-Kal MH, Hunink MG.

Med Decis Making. 2010 Mar-Apr;30(2):194-205. doi: 10.1177/0272989X09342277.

PMID:
20190188
19.

Clinical trial optimization: Monte Carlo simulation Markov model for planning clinical trials recruitment.

Abbas I, Rovira J, Casanovas J.

Contemp Clin Trials. 2007 May;28(3):220-31.

PMID:
16979387
20.

Personalized prophylactic anticoagulation decision analysis in patients with membranous nephropathy.

Lee T, Biddle AK, Lionaki S, Derebail VK, Barbour SJ, Tannous S, Hladunewich MA, Hu Y, Poulton CJ, Mahoney SL, Charles Jennette J, Hogan SL, Falk RJ, Cattran DC, Reich HN, Nachman PH.

Kidney Int. 2014 Jun;85(6):1412-20. doi: 10.1038/ki.2013.476.

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