Analysis of Traditional Chines Medicine Using Prescription Function Prediction

Ahmad Hameed, Sayed Saleh, Foud Monem

Abstract


Determining a prescription’s function is one of the challenging problems in Traditional Medicine (TCM). In past decades, TCM has been widely researched through various methods in computer science, but none concentrates on the prediction method for a new prescription’s function. In this study, two methods are presented concerning this issue. The first method is based on a novel supervised topic model named Label-Prescription-Herb (LPH), which incorporates herb-herb compatibility rules into learning process. The second method is based on multilabel classifiers built by TFIDF

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