OBJECTIVE: To explore the features of Traditional Chinese Medicine(TCM) syndromes in male infertility using computer-based analyses.METHODS: Latent class analysis was used to analyze the TCM syndrome data from 813 pat...OBJECTIVE: To explore the features of Traditional Chinese Medicine(TCM) syndromes in male infertility using computer-based analyses.METHODS: Latent class analysis was used to analyze the TCM syndrome data from 813 patients with male infertility and establish a latent tree model.RESULTS: A latent tree model with a Bayesian information criterion score of-11 263 was created.This model revealed that the characteristics of basic TCM syndromes in patients with male infertility were kidney Yang deficiency, kidney Qi deficiency,spleen Yang deficiency, liver Qi stagnation, Qi stagnation and blood stasis, and dump-heat; moreover,most patients with male infertility had complex syndromes(spleen-kidney Yang deficiency and liver Qi stagnation) rather than simple single syndromes.CONCLUSION: The hidden tree model analysis revealed the objective and quantitative complex relationships between the TCM symptoms of male infertility, and obtained the quantification and objective evidence of TCM syndromes in male infertility.展开更多
Latent Semantic Analysis involves natural language processing techniques for analyzing relationships between a set of documents and the terms they contain, by producing a set of concepts (related to the documents and ...Latent Semantic Analysis involves natural language processing techniques for analyzing relationships between a set of documents and the terms they contain, by producing a set of concepts (related to the documents and terms) called semantic topics. These semantic topics assist search engine users by providing leads to the more relevant document. We develope a novel algorithm called Latent Semantic Manifold (LSM) that can identify the semantic topics in the high-dimensional web data. The LSM algorithm is established upon the concepts of topology and probability. Asearch tool is also developed using the LSM algorithm. This search tool is deployed for two years at two sites in Taiwan: 1) Taipei Medical University Library, Taipei, and 2) Biomedical Engineering Laboratory, Institute of Biomedical Engineering, National Taiwan University, Taipei. We evaluate the effectiveness and efficiency of the LSM algorithm by comparing with other contemporary algorithms. The results show that the LSM algorithm outperforms compared with others. This algorithm can be used to enhance the functionality of currently available search engines.展开更多
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...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.展开更多
基金Supported by the Beijing University of Traditional Chinese Medicine Foundation(No.2015-JYB-JSMS099)the National Science Foundation of China(No.81473527)
文摘OBJECTIVE: To explore the features of Traditional Chinese Medicine(TCM) syndromes in male infertility using computer-based analyses.METHODS: Latent class analysis was used to analyze the TCM syndrome data from 813 patients with male infertility and establish a latent tree model.RESULTS: A latent tree model with a Bayesian information criterion score of-11 263 was created.This model revealed that the characteristics of basic TCM syndromes in patients with male infertility were kidney Yang deficiency, kidney Qi deficiency,spleen Yang deficiency, liver Qi stagnation, Qi stagnation and blood stasis, and dump-heat; moreover,most patients with male infertility had complex syndromes(spleen-kidney Yang deficiency and liver Qi stagnation) rather than simple single syndromes.CONCLUSION: The hidden tree model analysis revealed the objective and quantitative complex relationships between the TCM symptoms of male infertility, and obtained the quantification and objective evidence of TCM syndromes in male infertility.
文摘Latent Semantic Analysis involves natural language processing techniques for analyzing relationships between a set of documents and the terms they contain, by producing a set of concepts (related to the documents and terms) called semantic topics. These semantic topics assist search engine users by providing leads to the more relevant document. We develope a novel algorithm called Latent Semantic Manifold (LSM) that can identify the semantic topics in the high-dimensional web data. The LSM algorithm is established upon the concepts of topology and probability. Asearch tool is also developed using the LSM algorithm. This search tool is deployed for two years at two sites in Taiwan: 1) Taipei Medical University Library, Taipei, and 2) Biomedical Engineering Laboratory, Institute of Biomedical Engineering, National Taiwan University, Taipei. We evaluate the effectiveness and efficiency of the LSM algorithm by comparing with other contemporary algorithms. The results show that the LSM algorithm outperforms compared with others. This algorithm can be used to enhance the functionality of currently available search engines.
基金Supported by Program of Beijing Municipal S&T Commission, China(No.D08050703020803,D08050703020804)China NSFC Project(No.90709006)+1 种基金National Key Technology R&D Program k(2007BA110B06)China 973 Project(No.2011CB505101)
文摘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.
