Title: Modelling traditional Chinese medicine therapy planning with POMDP

Authors: Qi Feng; Xuezhong Zhou; Houkuan Huang; Xiaoping Zhang; Runshun Zhang

Addresses: National Natural Science Foundation of China, Beijing 100085, China ' School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China ' School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China ' China Academy of Chinese Medical Sciences, Beijing 100700, China ' Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China

Abstract: During the traditional Chinese medicine (TCM) treatment procedure, the manifestations of patients could be observed but the health state and TCM diagnosis of patient are uncertain. Thus, the real-world TCM therapy planning is a typical kind of dynamic decision making under uncertainty. Partially observable Markov decision process (POMDP) constitutes a powerful mathematical model for planning and is suitable for TCM therapy planning. In this paper, we apply POMDP to solve TCM therapy planning problem with all the dynamics inferred from TCM clinical data for type 2 diabetes treatment. This POMDP model contains 55 health states, 67 observation variables and 414 actions, it could order prescriptions for patients with type 2 diabetes. The results demonstrate that the POMDP model for TCM therapy planning is reasonable and helpful in clinical practice.

Keywords: POMDP; partially observable Markov decision process; clinical decision making; therapy planning; TCM; traditional Chinese medicine; dynamic decision making; uncertainty; mathematical modelling; type 2 diabetes; diabetes treatment; clinical practice.

DOI: 10.1504/IJFIPM.2013.057405

International Journal of Functional Informatics and Personalised Medicine, 2013 Vol.4 No.2, pp.145 - 166

Received: 09 May 2013
Accepted: 17 Aug 2013
Published online: 29 Oct 2013 *

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