Extracting Predictive Indicator for Prognosis of Cerebral Infarction Using Machine Learning Techniques

摘要：

　　Identifying important predicative indicators for prognosis is useful since these factors help for understanding diseases and determining treatments for patients.We extracted important factors for prognosis of cerebral infarction from EHR.We analyzed EHR data of 1,697 patients with 1,602 variables using gradient boosting decision tree.Extracted factors include not only well-known factors such as NIHSS but also new factors such as albumin-globulin ratio.

关键词： Prognosis Cerebral Infarction Machine Learning

作者: Yasunobu Nohar Koutarou Matsumoto Naoki Nakashima

作者单位: Medical Information Center,Kyushu University Hospital,Fukuoka,Japan Saiseikai Kumamoto Hospital,Kumamoto,Japan

会议类型: 国际会议

会议名称: 第十六届世界医药健康信息学大会((MEDINFO2017)、第二届世界医药健康信息学华语论坛(WCHIS 2017)、第15届全国医药信息学大会(CMIA 2017)

会议地点: 苏州

会议语种:英文

页码: 1280-1280

在线出版日期: 2017-08-21（万方平台首次上网日期，不代表论文的发表时间）