Modeling hybrid rough set-based classification procedures to identify hemodialysis adequacy for end-stage renal disease patients

被引:10
作者
Chen, You-Shyang [1 ]
机构
[1] Hwa Hsia Inst Technol, Dept Informat Management, New Taipei City 235, Taiwan
关键词
End-Stage Renal Disease (ESRD); HemoDialysis (HD) adequacy; Urea Reduction Ratio (URR); Rough Set Theory (RST); Feature selection; Classification model; ADULT POPULATION; SELECTION; CLASSIFIERS; DETERMINANTS; RULES;
D O I
10.1016/j.compbiomed.2013.08.001
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Healthcare problems observed in the majority of end-stage renal disease (ESRD) patients regarding hemodialysis (HD) treatment are serious issues for the Taiwanese healthcare services, and an interesting topic is thus the adequacy of HD therapy. This study successfully models a hybrid procedure to measure HD adequacy to assess therapeutic effects and to explore the relationship between accuracy and coverage for interested parties. The proposed model has better accuracy, a lower standard deviation, and fewer attributes than the listed methods under various evaluation criteria. The study results are useful to subsequent researchers to develop suitable applications, and to ESRD patients and their doctors to ensure satisfactory medical quality. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1590 / 1605
页数:16
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