External Validation of Two Classification and Regression Tree Models to Predict the Outcome of Inpatient Cardiopulmonary Resuscitation

Journal of Intensive Care Medicine

Volumn 32, Issue 5, 2017, Pages 333-338

  Guilbault, Ryan W R ^a   Ohlsson, Marcus Andreas ^b   Afonso, Anna M ^c   Ebell, Mark H ^d  

^a MERCER UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b LUND UNIVERSITY   (Sweden)

^c DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d UNIVERSITY OF GEORGIA   (United States)

Author keywords

cardiac arrest; cardiopulmonary resuscitation; classification and regression tree; clinical decision rule

Indexed keywords

ACCURACY; ADULT; AGED; ALGORITHM; AREA UNDER THE CURVE; ARTICLE; BRAIN FUNCTION; CLASSIFICATION AND REGRESSION TREE MODEL; CLINICAL DECISION MAKING; CLINICAL DECISION SUPPORT SYSTEM; CONTROLLED STUDY; DIAGNOSTIC TEST ACCURACY STUDY; FEMALE; HIGH RISK PATIENT; HOSPITAL PATIENT; HUMAN; LOW RISK PATIENT; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROSPECTIVE STUDY; RECEIVER OPERATING CHARACTERISTIC; REGRESSION ANALYSIS; RESUSCITATION; TREATMENT OUTCOME; VALIDATION STUDY; DECISION SUPPORT SYSTEM; HEART ARREST; MIDDLE AGED; MORTALITY; PROCEDURES; STATISTICS AND NUMERICAL DATA;

AGED; ALGORITHMS; AREA UNDER CURVE; CARDIOPULMONARY RESUSCITATION; DECISION SUPPORT TECHNIQUES; FEMALE; HEART ARREST; HUMANS; INPATIENTS; MALE; MIDDLE AGED; PROSPECTIVE STUDIES; REGRESSION ANALYSIS; ROC CURVE; TREATMENT OUTCOME;

EID: 85019134382     PISSN: 08850666     EISSN: 15251489     Source Type: Journal    
DOI: 10.1177/0885066616686924     Document Type: Article

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