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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Functional Informatics and Personalised Medicine
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
