The K-nearest neighbor algorithm predicted rehabilitation potential better than current Clinical Assessment Protocol

Journal of Clinical Epidemiology

Volumn 60, Issue 10, 2007, Pages 1015-1021

  Zhu, Mu ^a   Chen, Wenhong ^a   Hirdes, John P ^a,b   Stolee, Paul ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

^b Homewood Health Centre Guelph   (Canada)

Author keywords

Bayes' theorem; Clinical decision making; Diagnostic likelihood ratio; InterRAI; Machine learning; Rehabilitation

Indexed keywords

ALGORITHM; ARTICLE; CLINICAL ASSESSMENT; COMMUNITY CARE; COMPUTER MODEL; DATA BASE; DECISION MAKING; FOLLOW UP; HOME CARE; HUMAN; MACHINE LEARNING; MEDICAL INFORMATION; PRIORITY JOURNAL; REHABILITATION CARE;

ACTIVITIES OF DAILY LIVING; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; DECISION MAKING, COMPUTER-ASSISTED; DIAGNOSTIC ERRORS; HEALTH STATUS INDICATORS; HOME CARE SERVICES; HUMANS; ONTARIO; PATIENT SELECTION; PROGNOSIS; REHABILITATION;

EID: 34548623814     PISSN: 08954356     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jclinepi.2007.06.001     Document Type: Article

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