A comparison of risk prediction methods using repeated observations: an application to electronic health records for hemodialysis

Statistics in Medicine

Volumn 36, Issue 17, 2017, Pages 2750-2763

  Goldstein, Benjamin A ^a,c   Pomann, Gina Maria ^a   Winkelmayer, Wolfgang C ^b   Pencina, Michael J ^a,c  

^a DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b BAYLOR COLLEGE OF MEDICINE   (United States)

^c DUKE CLINICAL RESEARCH INSTITUTE   (United States)

Author keywords

clinical risk prediction; electronic health records; end stage renal disease; functional data analysis; hemodialysis; joint models; longitudinal data

Indexed keywords

ARTICLE; DATA ANALYSIS; ELECTRONIC HEALTH RECORD; END STAGE RENAL DISEASE; FOLLOW UP; HEMODIALYSIS; HUMAN; INTERMETHOD COMPARISON; LONGITUDINAL STUDY; MACHINE LEARNING; MORTALITY; OBSERVATIONAL STUDY; PREDICTOR VARIABLE; RISK ASSESSMENT; STATISTICAL ANALYSIS; ALGORITHM; BIOMETRY; COMPARATIVE STUDY; COMPUTER SIMULATION; MONTE CARLO METHOD; PROCEDURES; SURVIVAL ANALYSIS;

ALGORITHMS; BIOMETRY; COMPUTER SIMULATION; ELECTRONIC HEALTH RECORDS; HUMANS; MONTE CARLO METHOD; RENAL DIALYSIS; RISK ASSESSMENT; SURVIVAL ANALYSIS;

EID: 85018742981     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.7308     Document Type: Article

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