Planning treatment of ischemic heart disease with partially observable Markov decision processes
Planning treatment of ischemic heart disease with partially observable Markov decision processes
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DOI：
10.1016/s0933-3657(99)00042-1
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发表时间：
2000-03-01
影响因子：
7.5
通讯作者：
Fraser, H
中科院分区：
文献类型：
--
作者：
Hauskrecht, M;Fraser, H
一种疾病的诊断和治疗不是分开的、一次性的活动。相反，随着时间的推移，它们往往是相互依赖和交织的。这主要是由于对潜在疾病的不确定性，与患者对治疗的反应相关的不确定性，以及不同诊断(调查)和治疗程序的不同成本。在运筹学、控制理论和人工智能领域发展和使用的部分可观测马尔可夫决策过程(POMDP)框架特别适合于对这样一个复杂的决策过程进行建模。在本文中，我们展示了如何使用POMDP框架来建模和解决缺血性心脏病(IHD)患者的管理问题，并展示了该框架相对于标准决策形式主义的建模优势。(C)2000 Elsevier Science B.V.保留所有权利。
Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead, they are very often dependent and interleaved over time. This is mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of partially observable Markov decision processes (POMDPs) developed and used in the operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In this paper, we show how the POMDP framework can be used to model and solve the problem of the management of patients with ischemic heart disease (IHD), and demonstrate the modeling advantages of the framework over standard decision formalisms. (C) 2000 Elsevier Science B.V. All rights reserved.