Construction Of Database System And Data Mining Researching Of Professor Ban Xiuwen Treating On Leukorrhagia

Professor Ban Xiuwen is the famous gynecologist, one of the first group of famousveteran teran doctors of TCM and one of the first group of Traditional Chinese MedicalScience Master. During seventy years of practicing medicine course, he is expert in internalmedicine, department of gynecology, pediatrics, acupuncture and so on. He has greataccomplishments in menses, morbid leukorrhea, gravidity, postpartum and aciesis ofgynecology. Unscrambling and digging deeply of the academic thought and practiceexperience of Traditional Chinese Medical Science Master, inhered it and innovatedunceasing, which has important meaning of promoting Chinese medical science enterprise.This research obtained all the clinical medical records of551medical records,733casesof examine, which are meet the criterion by collecting systematically, unscrambling,analyzing Professor Ban Xiuwen’s clinical diagnosing and treating records of morbidleucorrhea and bolting according to the standard of Chinese medical science medical recordinternalizing, obviating. The exploitation felicities is Microsoft Visual Studio2008, basing onWindows Server2008R2operating system and Microsoft SQL Server2008R2databaseadministration platform, using B/S technique to build database system of Professor BanXiuwen’s morbid leucorrhea diagnosing and treating. This study has realized the entering,searching, revising and clinical aided diagnosis and treatment of Professor Ban Xiuwen’sdiagnosing and treating medical records of morbid leucorrhea.Evolving the retrospective studies of Professor Ban Xiuwen’s clinical records of morbidleucorrhea and experience basis on the database system, I summarize his characteristictreatment determination experience according to medical records essential informationanalyst,drugs association analysis,medicine and symptom-complex by means of statisticalanalysis and data mining. At the same time, his treatment determination experience of morbidleucorrhea has got a good corroboration in the result of clinical medical records statisticalanalysis and data mining.