A Topic Modeling Approach for Traditional Chinese Medicine Prescriptions

In traditional Chinese medicine (TCM), prescriptions are the daughters of doctors' clinical experiences, which have been the main way to cure diseases in China for several thousand years. In the long Chinese history, a large number of prescriptions have been invented based on TCM theories. Regularities in the prescriptions are important for both clinical practice and novel prescription development. Previous works used many methods to discover regularities in prescriptions, but rarely described how a prescription is generated using TCM theories. In this work, we propose a topic model which characterizes the generative process of prescriptions in TCM theories and further incorporate domain knowledge into the topic model. Using 33,765 prescriptions in TCM prescription books, the model can reflect the prescribing patterns in TCM. Our method can outperform several previous topic models and group recommendation methods on generalization performance, herbs recommendation, symptoms suggestion, and prescribing patterns discovery.