title: Modeling hybrid rough set-based classification procedures to identify hemodialysis adequacy for end-stage renal disease patients.
abstract: 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.
authors.affiliation: Department of Information Management, Hwa Hsia Institute of Technology, 111, Gong Jhuan Road, Chung Ho District, New Taipei City 235, Taiwan. Electronic address: ys_chen@cc.hwh.edu.tw.
authors.forename: You-Shyang
authors.initials: YS
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D005260:Female; D006801:Humans; D007676:Kidney Failure, Chronic / Q000503:physiopathology* / Q000628:therapy*; D008297:Male; D008490:Medical Informatics / Q000379:methods*; D008954:Models, Biological; D006435:Renal Dialysis; D018709:Statistics, Nonparametric
keywords: Classification model; End-Stage Renal Disease (ESRD); Feature selection; HemoDialysis (HD) adequacy; Rough Set Theory (RST); Urea Reduction Ratio (URR)