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作 者:叶桦[1] 冯全生[1] 严小英[1] 赵亮[1] YE Hua;FENG Quan-sheng;YAN Xiao-ying;ZHAO Liang(Chengdu University of TCM,Chengdu 611137,China)
机构地区:[1]成都中医药大学,成都611137
出 处:《中华中医药杂志》2020年第10期5184-5187,共4页China Journal of Traditional Chinese Medicine and Pharmacy
基 金:四川省科技计划应用基础研究项目(No.2019YJ0374);国家重点研发计划中医药现代化研究(No.2018YFC1704104);2019年四川省卫生信息学会科研课题(No.2019-09);成都中医药大学中医药信息化研究专项重点项目(No.MIEC1804)。
摘 要:目的:提出一种基于拟牛顿法的糖尿病合并冠心病舌脉象证型预测的人工神经网络(ANN)模型,为中医智能辨证提供新的思路和方法。方法:以四川省"中医数字化诊疗平台"门诊临床电子病历3233例作为数据集,经过数据验证、规范和标化后,运用拟牛顿法构建舌脉象智能辨证的反向传播神经网络(BPNN)模型。结果:气阴亏虚(836例)和气阴两虚夹瘀血(1353例)证型辨证准确率较高,分别为99.31%、75.60%。结论:舌脉象智能辨证模型在数据量较大的情况下,表现出优秀的证型预测能力,说明该模型在中医临床辅助诊断系统上的应用具有可行性。Objective:A artificial neural network(ANN)model of tongues and pulses syndrome differentiation in traditional Chinese medicine(TCM)for diabetes mellitus(DN)with coronary heart disease(CHD)patients based on QuasiNewton method is proposed in this paper.It will provide a new idea and method of the intelligent syndrome differentiation in TCM.Methods:A total of 3233 cases data of the clinical electronic medical record collected from the’TCM Digital Diagnosis and Treatment Platform’of Sichuan was used as the data set.After verifying data accuracy and standardizing data,a back propagation neural network(BPNN)model of tongues and pulses intelligent syndrome differentiation in TCM was built by using Quasi-Newton method.Results:The accuracy of deficiency of both qi and yin syndrome(836 cases)was 99.31%and the accuracy of deficiency of both qi and yin with blood stasis syndrome(1353 cases)was 75.60%.Conclusion:The intelligent syndrome differentiation model of tongues and pulses shows excellent syndrome type prediction ability in the case of large amount of data,that it is feasible to be applied in the clinical auxiliary diagnosis system of TCM.
关 键 词:糖尿病合并冠心病 舌脉象辨证 人工神经网络 拟牛顿法 反向传播神经网络 中医智能
分 类 号:R259[医药卫生—中西医结合]
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