Supervised machine learning for the prediction of infection on admission to hospital: A prospective observational cohort study

Journal of Antimicrobial Chemotherapy

Volumn 74, Issue 4, 2019, Pages 1108-1115

  Rawson, T M ^a,b   Hernandez, B ^c   Moore, L S P ^a,b   Blandy, O ^a   Herrero, P ^c   Gilchrist, M ^b   Gordon, A ^c   Toumazou, C ^c   Sriskandan, S ^a,b   Georgiou, P ^c   Holmes, A H ^a,b  

^a The National Institute for Health Research Health Protection Research Unit in Blood Borne and Sexually Transmitted Infections at University College London in partnership with UK Health Security Agency   (United Kingdom)

^b HAMMERSMITH HOSPITAL   (United Kingdom)

^c IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALANINE AMINOTRANSFERASE; ALKALINE PHOSPHATASE; ANTIBIOTIC AGENT; BILIRUBIN; C REACTIVE PROTEIN; CREATININE; BIOLOGICAL MARKER;

ADULT; AGED; ALANINE AMINOTRANSFERASE BLOOD LEVEL; ALKALINE PHOSPHATASE BLOOD LEVEL; ARTICLE; BACTERIAL INFECTION; BILIRUBIN BLOOD LEVEL; BLOOD SAMPLING; COHORT ANALYSIS; COMMUNITY ACQUIRED INFECTION; CREATININE BLOOD LEVEL; FEMALE; FOLLOW UP; HOSPITAL ADMISSION; HOSPITAL INFECTION; HUMAN; LEUKOCYTE COUNT; MAJOR CLINICAL STUDY; MALE; OBSERVATIONAL STUDY; PRESCRIPTION; PROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; SUPERVISED MACHINE LEARNING; ALGORITHM; BLOOD EXAMINATION; CLINICAL DECISION MAKING; CLINICAL DECISION SUPPORT SYSTEM; DIAGNOSIS; DIAGNOSTIC TEST; DISEASE MANAGEMENT; EPIDEMIOLOGY; ETIOLOGY; MIDDLE AGED; PROCEDURES; PROGNOSIS; RECEIVER OPERATING CHARACTERISTIC; VERY ELDERLY; YOUNG ADULT;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; BIOMARKERS; CLINICAL DECISION-MAKING; COHORT STUDIES; DECISION SUPPORT SYSTEMS, CLINICAL; DIAGNOSTIC TESTS, ROUTINE; DISEASE MANAGEMENT; FEMALE; FOLLOW-UP STUDIES; HEMATOLOGIC TESTS; HUMANS; INFECTIONS; MALE; MIDDLE AGED; PATIENT ADMISSION; PROGNOSIS; ROC CURVE; SUPERVISED MACHINE LEARNING; YOUNG ADULT;

EID: 85063012496     PISSN: 03057453     EISSN: 14602091     Source Type: Journal    
DOI: 10.1093/jac/dky514     Document Type: Article

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