ENABLING UBIQUITOUS DATA MINING IN INTENSIVE CARE Features Selection and Data Pre-processing

摘要：

Ubiquitous Data Mining and Intelligent Decision Support Systems are gaining interest by both computer science researchers and intensive care doctors. Previous work contributed with Data Mining models to predict organ failure and outcome of patients in order to support and guide the clinical decision based on the notion of critical events and the data collected from monitors in real-time. This paper addresses the study of the impact of the Modified Early Warning Score, a simple physiological score that may allow improvements in the quality and safety of management provided to surgical ward patients, in the prediction sensibility. The feature selection and data pre-processing are also detailed. Results show that for some variables associated to this score the impact is minimal.

关键词： Ubiquitous Data Mining Real-time Intelligent Decision Support Systems Organ failure prediction Clinical Data Mining Intensive Care Environment

作者: Manuel Santos Filipe Portela

作者单位: Departamento de Sistemas de Informac(a)o, Universidade do Minho, Guimar(a)es, Portugal

会议类型: 国际会议

会议名称: 13th International Conference on Enterprise Information System(第13届企业信息系统国际会议 ICEIS 2011)

会议地点: 北京

会议语种:英文

页码: 2147-2152

在线出版日期: 2011-06-08（万方平台首次上网日期，不代表论文的发表时间）