Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis

Journal of the American Medical Informatics Association

Volumn 22, Issue 4, 2015, Pages 872-880

  Perotte, Adler ^a   Ranganath, Rajesh ^b   Hirsch, Jamie S ^a   Blei, David ^a   Elhadad, Noémie ^a  

^a Och Spine at New York Presbyterian Hospitals   (United States)

^b Princeton University   (United States)

Author keywords

Electronic health records; Risk prediction; Survival analysis; Topic modeling

Indexed keywords

ACCURACY; AGED; ARTICLE; CHRONIC KIDNEY DISEASE; COHORT ANALYSIS; DEMOGRAPHY; DISEASE COURSE; ELECTRONIC MEDICAL RECORD; FEMALE; GLOMERULUS FILTRATION RATE; HOSPITAL PATIENT; HUMAN; KALMAN FILTER RISK MODEL; LABORATORY DIAGNOSIS; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; MEDICAL INFORMATION; OUTPATIENT; PRIMARY MEDICAL CARE; PROPORTIONAL HAZARDS MODEL; RETROSPECTIVE STUDY; RISK ASSESSMENT; STATISTICAL ANALYSIS; STATISTICAL MODEL; SURVIVAL; TIME SERIES ANALYSIS; CHRONIC KIDNEY FAILURE; MIDDLE AGED; PATHOPHYSIOLOGY; PRIMARY HEALTH CARE; THEORETICAL MODEL; TIME;

AGED; COHORT STUDIES; DISEASE PROGRESSION; ELECTRONIC HEALTH RECORDS; FEMALE; GLOMERULAR FILTRATION RATE; HUMANS; LONGITUDINAL STUDIES; MALE; MIDDLE AGED; MODELS, THEORETICAL; PRIMARY HEALTH CARE; PROPORTIONAL HAZARDS MODELS; RENAL INSUFFICIENCY, CHRONIC; RISK ASSESSMENT; SURVIVAL ANALYSIS; TIME;

EID: 84940373302     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1093/jamia/ocv024     Document Type: Article

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