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Title:: The Development of Polycystic Ovarian Syndrome ?Auxiliary Diagnostic System

Author(s):: ZHANG Haowei; WANG Zinan ; LIU Ying; SUN Yangyang; School of Medical Instrument and Food Engineering,University of Shanghai for Science and Technology，Shanghai 200093，China

Keywords:: Traditional Chinese medicine; PCOS; Logistic regression analysis; Data mining; Auxiliary diagnose; Classification

摘要:: 开发多囊卵巢综合症辅助诊断系统，帮助医生诊断多囊卵巢综合症患者的类型。根据大量多囊卵巢综合症患者症候和证型的数据，从中总结出对应关系，以期通过症候判断患者所属的证型。多囊卵巢综合症患者分类效果良好。其中Logistic算法的正确率为93.5%。设计出的多囊卵巢综合症辅助诊断系统科学合理、简单易用、具有实际指导意义。

Abstract:: Developingcomputer-aideddiagnosissystemto help the doctor to classify the patientswith polycystic ovary syndrome.According to the data of a large number of patients with polycystic ovary syndrome and syndrome types, the corresponding relationship was summed up, in order to determine the syndrome types of the patients.Patients with polycystic ovary syndrome has a good classification effect. The correct rate of Logistic algorithm is 93.5%.The design of PCOS auxiliary diagnostic system is scientific and reasonable, simple and easy to use, with practical guiding significance.