Probabilistic models for optimizing patients survival rates

DOI10.1080/09720502.2008.10700595zbMath1160.60331OpenAlexW2082940158MaRDI QIDQ3604036

Dimitrios I. Stengos, J. E. Goulionis, George Tzavelas

Publication date: 24 February 2009

Published in: Journal of Interdisciplinary Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/09720502.2008.10700595

zbMATH Keywords

dynamic programmingMarkov processesOR in medicine

Mathematics Subject Classification ID

Dynamic programming (90C39) Medical applications (general) (92C50) Applications of renewal theory (reliability, demand theory, etc.) (60K10)

Related Items (1)

The partially observable Markov decision processes in healthcare: an application to patients with ischemic heart disease (IHD)

Cites Work

• Unnamed Item
• Dynamic programming and stochastic control
• Finite state approximation algorithms for average cost denumerable state Markov decision processes
• Optimal control of Markov processes with incomplete state information
• Optimization of stochastic systems. Topics in discrete-time systems
• On the Use of Replacements to Extend System Life
• Contraction Mappings in the Theory Underlying Dynamic Programming

This page was built for publication: Probabilistic models for optimizing patients survival rates