A new severity of illness scale using a subset of acute physiology and chronic health evaluation data elements shows comparable predictive accuracy

Critical Care Medicine

Volumn 41, Issue 7, 2013, Pages 1711-1718

  Johnson, Alistair E W ^a   Kramer, Andrew A ^b   Clifford, Gari D ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b CERNER CORPORATION   (United States)

Author keywords

APACHE; data mining; mortality; predictive models; severity of illness

Indexed keywords

ACCURACY; AGE; APACHE; ARTICLE; CRITICALLY ILL PATIENT; ELECTIVE SURGERY; HOSPITAL ADMISSION; HUMAN; INTENSIVE CARE UNIT; LEARNING ALGORITHM; LENGTH OF STAY; MACHINE LEARNING; MAJOR CLINICAL STUDY; MORTALITY; OXFORD ACUTE SEVERITY OF ILLNESS SCORE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SCORING SYSTEM;

APACHE; ARTIFICIAL INTELLIGENCE; CHRONIC DISEASE; CONTINENTAL POPULATION GROUPS; FEMALE; HEALTH STATUS INDICATORS; HUMANS; INTENSIVE CARE UNITS; LENGTH OF STAY; MALE; MIDDLE AGED; RETROSPECTIVE STUDIES; ROC CURVE; SENSITIVITY AND SPECIFICITY;

EID: 84880558601     PISSN: 00903493     EISSN: 15300293     Source Type: Journal    
DOI: 10.1097/CCM.0b013e31828a24fe     Document Type: Article

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