A quantitative system for pulse diagnosis in Traditional Chinese Medicine

The pulse diagnosis is one of the most important examinations in Traditional Chinese Medicine (TCM). Due to the subjectivity and fuzziness of pulse diagnosis in TCM, quantitative systems or methods are needed to modernize pulse diagnosis. But up to now, the effective models that can classify pulse types according to pulse waves automatically have not been reported, which undoubtedly limits the practical applications of pulse diagnosis in clinical medicines. In this article, a novel quantitative system for pulse diagnosis was constructed based on Bayesian networks (BNs) to build the mapping relationships between pulse waves and pulse types. The results show that the system obtains relative reliable predictions of pulse types, and its predictive accuracy rate reach 84%, which testifies that the model used in our system is feasible and effective and can be expected to facilitate popular applications of TCM.