摘要
Chinese medicine （CM） is a discipline with its own distinct methodologies and philosophical principles. The main method of treatment in CM is to use herbal prescriptions. Typically, a number of herbs are combined to form a formula and different formulae are prescribed for different patients. Regularities in the mixture of herbs in the prescriptions are important for both clinical treatment and novel patent medicine development. In this study, we analyze CM formula data using latent tree （LT） models. Interesting regularities are discovered. Those regularities are of interest to students of CM as well as pharmaceutical companies that manufacture medicine using Chinese herbs.
Chinese medicine （CM） is a discipline with its own distinct methodologies and philosophical principles. The main method of treatment in CM is to use herbal prescriptions. Typically, a number of herbs are combined to form a formula and different formulae are prescribed for different patients. Regularities in the mixture of herbs in the prescriptions are important for both clinical treatment and novel patent medicine development. In this study, we analyze CM formula data using latent tree （LT） models. Interesting regularities are discovered. Those regularities are of interest to students of CM as well as pharmaceutical companies that manufacture medicine using Chinese herbs.
基金
Supported by Program of Beijing Municipal S&T Commission, China(No.D08050703020803,D08050703020804)
China NSFC Project(No.90709006)
National Key Technology R&D Program k(2007BA110B06)
China 973 Project(No.2011CB505101)
