Modelling traditional Chinese medicine therapy planning with POMDP

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.