| Discovery of diagnosis pattern of coronary heart disease with qi deficiency syndrome by the T-test-based adaboost algorithm. | |
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MedLine Citation:
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PMID: 21876710 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Coronary heart disease (CHD) is still the leading cause of death for adults worldwide. Traditional Chinese medicine (TCM) has a history of 1000 years fighting against the disease and provides a complementary and alternative treatment to it. Syndrome is the core of TCM diagnosis and it is traditionally diagnosed based on macroscopic symptoms as well as tongue and pulse recognitions of patients. Establishment of the diagnosis method in the microcosmic level is an urgent and major problem in TCM. The aim of this study was to establish characteristic diagnosis pattern for CHD with Qi deficiency syndrome (QDS). Thirty-four biological parameters were detected in 52 patients having unstable angina (UA) with or without QDS. Then, we presented a novel data mining method, t-test-based Adaboost algorithm, to establish highest prediction accuracy with the least number of biological parameters for UA with QDS. We gained a pattern composed of five biological parameters that distinguishes UA with QDS patients from non-QDS patients. The diagnosis accuracy of the patterns could reach 84.5% based on a 3-fold cross validation technique. Moreover, we included 85 UA cases collected from hospitals located in the north and south of China to further verify the association between the pattern and QDS. The classification accuracy is 83.5%, which keeps consistent with the accuracy obtained by the cross-validation technique. The association between a symptom and the five biological parameters was established by the data mining method and it reached an accuracy of ∼80%. These results showed that the t-test-based Adaboost algorithm might be a powerful technique for diagnosing syndrome in TCM in the context of CHD. |
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Authors:
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Huihui Zhao; Jianxin Chen; Na Hou; Peng Zhang; Yong Wang; Jing Han; Qin Hou; Qige Qi; Wei Wang |
Publication Detail:
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Type: Journal Article Date: 2011-08-21 |
Journal Detail:
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Title: Evidence-based complementary and alternative medicine : eCAM Volume: 2011 ISSN: 1741-4288 ISO Abbreviation: Evid Based Complement Alternat Med Publication Date: 2011 |
Date Detail:
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Created Date: 2011-08-30 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101215021 Medline TA: Evid Based Complement Alternat Med Country: United States |
Other Details:
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Languages: eng Pagination: 408650 Citation Subset: - |
Affiliation:
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Beijing University of Chinese Medicine, Beijing 100029, China. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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