CORC  > 北京大学  > 工学院
Mortality prediction of ICU patients using EDA-enhanced logistic model
Chen, Lili ; Zhang, Xi ; Xu, Xiaoyun ; Zhao, Liang
刊名international journal of services operations and informatics
2012
DOI10.1504/IJSOI.2012.051402
英文摘要Due to the different health conditions of an increasing number of serious patients, the Intensive Care Unit (ICU) of a hospital has to correctly classify patients according to their conditions so that medical resources could be properly utilised. The seriousness of the illness can be classified based on the significant risk factors and its corresponding impacts on the patients' survival. How to quickly identify the significant variables is a major task for classification. This paper proposes a Multistage-EDA-Enhanced Logistic Regression (MEDAeLR) approach to precisely classify the patients and quickly diagnose with three-stage analysis. A cohort of 200 consecutive ICU patients was borrowed for validation. Regular MLR, classification trees and Linear Discriminant Analysis (LDA) are carried to compare the performance with proposed method. The results show that MEDAeLR provides more satisfactory identification performance in terms of Receiver Operating Characteristic (ROC) curve and Area under the ROC Curve (AUC). Copyright ? 2012 Inderscience Enterprises Ltd.; EI; 0; 2-3; 182-196; 7
语种英语
内容类型期刊论文
源URL[http://ir.pku.edu.cn/handle/20.500.11897/411401]  
专题工学院
推荐引用方式
GB/T 7714
Chen, Lili,Zhang, Xi,Xu, Xiaoyun,et al. Mortality prediction of ICU patients using EDA-enhanced logistic model[J]. international journal of services operations and informatics,2012.
APA Chen, Lili,Zhang, Xi,Xu, Xiaoyun,&Zhao, Liang.(2012).Mortality prediction of ICU patients using EDA-enhanced logistic model.international journal of services operations and informatics.
MLA Chen, Lili,et al."Mortality prediction of ICU patients using EDA-enhanced logistic model".international journal of services operations and informatics (2012).
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace