首页> 外文会议>International Conference on Natural Computation;ICNC '09 >Support Vector Machine (SVM) and Traditional Chinese Medicine: Syndrome Factors Based an SVM from Coronary Heart Disease Treated by Prominent Traditional Chinese Medicine Doctors
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Support Vector Machine (SVM) and Traditional Chinese Medicine: Syndrome Factors Based an SVM from Coronary Heart Disease Treated by Prominent Traditional Chinese Medicine Doctors

机译:支持向量机(SVM)和中药:基于冠心病SVM的综合症因素,由杰出的中医治疗

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Support vector machines (SVM) have been widely used in many scientific research fields. This paper introduces an original study about the treating experiences of prominent traditional Chinese medicine (TCM) doctors on coronary heart disease (CHD) using SVM, and to investigate the general laws of prominent TCM doctors for treating CHD. A database of diagnosing and treating CHD was set up on the basis of 115 typical medical records. The syndrome factors and relevant studies were analyzed by SVM (data mining software Weka 3.4 is used). The quantitative diagnosis was confirmed and CHD characteristics were explained. The laws of medicate administration for 8 syndrome factors were summed up from prominent TCM doctors. Application of SVM will help to reveal innate regularity of experience of prominent TCM doctors, and deeply understand the academic thinking of them, in order to improve the level of treatment for CHD with TCM.
机译:支持向量机(SVM)已广泛应用于许多科学研究领域。本文介绍了使用支持向量机对冠心病(CHD)杰出中医治疗经验的原始研究,并探讨了冠名中医治疗冠心病的一般规律。在115例典型病历的基础上,建立了冠心病诊治数据库。通过支持向量机(使用数据挖掘软件Weka 3.4)分析了证候因素和相关研究。定量诊断得到证实,并解释了冠心病特征。由著名的中医总结出8种综合症因素的药物管理规律。支持向量机的应用将有助于揭示中医名医的先天规律,深刻理解他们的学术思想,从而提高中医对冠心病的治疗水平。

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