教師資料查詢 | 類別: 期刊論文 | 教師: 蔣璿東 Chiang Ding-an (瀏覽個人網頁)

標題:Mining Medical Data: A Case Study of Endometriosis
學年101
學期2
出版(發表)日期2013/04/01
作品名稱Mining Medical Data: A Case Study of Endometriosis
作品名稱(其他語言)
著者Wang, Yi-Fan; Chang, Ming-Yang; Chiang, Rui-Dong; Hwang,Lain-Jinn; Lee, Cho-Ming; Wang, Yi-Hsin
單位淡江大學資訊工程學系
出版者New York: Springer New York LLC
著錄名稱、卷期、頁數Journal of Medical Systems 37(2), 9899(7pages)
摘要Ultrasound guided aspiration of ovarian endometrioma had been tried as an alternative therapeutic modality in patients whose desire to avoid surgery or surgical approach is contraindicated since 1991. Cyst puncture can reduce tumor volume and destruct the cyst wall, alleviate sticking circumstances and enhance the chance of recovery. But simple aspiration without other treatments results in high recurrence rate (28.5 % to 100 %). In order to reduce recurrence after aspiration, ultrasound-guided aspiration with instillation of tetracycline, methotrexate, and recombinant interleukin-2 has been combined and proven to be effective with the recurrence rates of 46.9 %, 18.1 %, and 40 % respectively. Noma et al. (2001) reported that conduct of ethanol instillation for more than 10 min particularly for a case with a single endometrial cyst is considered most effective from the standpoint of recurrence (14.9 %). Our goal is to analyze patients with recurrent pelvic cyst who underwent surgical intervention. The research data are based on clinical diagnosis, symptoms and medical intervention classification, and the cyst numbers are defined as forecast project target. The decision tree, methodology of data mining technology, is used to find the meaningful characteristic as well as each other mutually connection. The experimental result can help the clinical faculty doctors to better diagnose and provide treatment reference for future patients.
關鍵字Endometriosis; Data mining; Decision tree; Medical data
語言英文(美國)
ISSN0148-5598
期刊性質國外
收錄於SCI;
產學合作
通訊作者Wang, Yi-Fan; Wang, Yi-Hsin
審稿制度
國別美國
公開徵稿
出版型式,紙本
相關連結
Google+ 推薦功能,讓全世界都能看到您的推薦!