Application of rough set classifiers for determining hemodialysis adequacy in ESRD patients

Knowledge and Information Systems

Volumn 34, Issue 2, 2013, Pages 453-482

  Chen, You Shyang ^a   Cheng, Ching Hsue ^b  

^a HWA HSIA INSTITUTE OF TECHNOLOGY   (Taiwan)

^b NATIONAL YUNLIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

End stage renal disease (ESRD); Global method; Hemodialysis (HD) adequacy; Rough set theory; Urea reduction ratio (URR)

Indexed keywords

ARTIFICIAL INTELLIGENCE; DIALYSIS; DISEASES; FORECASTING; HEMODIALYZERS; KNOWLEDGE BASED SYSTEMS; METABOLISM; PATIENT TREATMENT; UREA;

ARTIFICIAL INTELLIGENCE TECHNIQUES; END STAGE RENAL DISEASE; GLOBAL METHODS; HEALTHCARE SERVICES; HEMODIALYSIS (HD) ADEQUACY; REAL-WORLD PROBLEM; ROUGH SET CLASSIFIERS; UREA REDUCTION RATIOS;

ROUGH SET THEORY;

EID: 84872597058     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-012-0490-0     Document Type: Article

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