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Traditional Chinese Medicine (TCM) multiple-acupoints stimulation is widely used to improve dysphagia among post-stroke patients. However, prior research in evidence-based acupuncture mostly focused on the treatment effects of single acupoint's on dysphagia, while the evidence of optimal sequence of multiple-acupoints stimulation remains limited. In this paper, we developed an evaluation method of hybrid knowledge (deterministic knowledge and the experiential group decision knowledge) sequences based on segmentation mechanism of sub-sequence fragments, and then, we proposed a Monte Carlo Tree Search (MCTS) sequential decision-making method under the hybrid knowledge. Thereafter, we applied this proposed sequential decision-making approach to optimizing sequential decision-making schema of multiple-acupoints stimulation, to treat dysphagia among post-stroke patients. Finally, we verified the validity and the feasibility of this method by comparing it to other sequential decision-making search methods.

A TCM acupoints ranking approach towards post-stroke dysphagia based on an improved MCTS decision method