Predicting readmission risk with institution-specific prediction models

Artificial Intelligence in Medicine

Volumn 65, Issue 2, 2015, Pages 89-96

  Yu, Shipeng ^a   Farooq, Faisal ^a   van Esbroeck, Alexander ^b   Fung, Glenn ^c   Anand, Vikram ^a   Krishnapuram, Balaji ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

^c American Family Insurance   (United States)

Author keywords

Predictive modeling; Readmission risk prediction

Indexed keywords

CARDIOLOGY; DIAGNOSIS; HEALTH INSURANCE; HOSPITAL DATA PROCESSING; HOSPITALS;

ACUTE MYOCARDIAL INFARCTION; CLASSIFICATION METHODS; METHODS AND MATERIALS; PERFORMANCE COMPARISON; PRECISION AND RECALL; PREDICTIVE MODELING; RISK PREDICTION MODELS; RISK PREDICTIONS;

FORECASTING;

ACCURACY; ACUTE HEART INFARCTION; ADULT; AGED; ARTICLE; CONCEPTUAL FRAMEWORK; DATA ANALYSIS; HEART FAILURE; HOSPITAL DISCHARGE; HOSPITAL PERSONNEL; HOSPITAL READMISSION; HUMAN; PNEUMONIA; PREDICTION; PRIORITY JOURNAL; RISK ASSESSMENT; SUPPORT VECTOR MACHINE; PROPORTIONAL HAZARDS MODEL; THEORETICAL MODEL;

HUMANS; MODELS, THEORETICAL; PATIENT READMISSION; PROPORTIONAL HAZARDS MODELS; RISK ASSESSMENT; SUPPORT VECTOR MACHINE;

EID: 84943583638     PISSN: 09333657     EISSN: 18732860     Source Type: Journal    
DOI: 10.1016/j.artmed.2015.08.005     Document Type: Article

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