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国家重点基础研究发展计划(2009ZX10005-019)

作品数:1 被引量:7H指数:1
发文基金:国家自然科学基金国家重点基础研究发展计划更多>>
相关领域:医药卫生更多>>

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Topic Model for Chinese Medicine Diagnosis and Prescription Regularities Analysis:Case on Diabetes被引量:7
2011年
Induction of common knowledge or regularities from large-scale clinical data is a vital task for Chinese medicine(CM).In this paper,we propose a data mining method,called the Symptom-Herb-Diagnosis topic(SHDT) model,to automatically extract the common relationships among symptoms,herb combinations and diagnoses from large-scale CM clinical data.The SHDT model is one of the multi-relational extensions of the latent topic model,which can acquire topic structure from discrete corpora(such as document collection) by capturing the semantic relations among words.We applied the SHDT model to discover the common CM diagnosis and treatment knowledge for type 2 diabetes mellitus(T2DM) using 3 238 inpatient cases.We obtained meaningful diagnosis and treatment topics(clusters) from the data,which clinically indicated some important medical groups corresponding to comorbidity diseases(e.g.,heart disease and diabetic kidney diseases in T2DM inpatients).The results show that manifestation sub-categories actually exist in T2DM patients that need specific,individualised CM therapies.Furthermore,the results demonstrate that this method is helpful for generating CM clinical guidelines for T2DM based on structured collected clinical data.
张小平周雪忠黄厚宽冯奇陈世波刘保延
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