Explainable machine-learning predictions for the prevention of hypoxaemia during surgery

Nature Biomedical Engineering

Volumn 2, Issue 10, 2018, Pages 749-760

  Lundberg, Scott M ^a   Nair, Bala ^b,c   Vavilala, Monica S ^b,c   Horibe, Mayumi ^d   Eisses, Michael J ^b,e   Adams, Trevor ^b,e   Liston, David E ^b,e   Low, Daniel King Wai ^b,e   Newman, Shu Fang ^b   Kim, Jerry ^b,e   Lee, Su In ^a  

^a University of Washington   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

^c UNIVERSITY OF WASHINGTON   (United States)

^d VA PUGET SOUND HEALTH CARE SYSTEM   (United States)

^e SEATTLE CHILDREN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANESTHESIOLOGY; ARTIFICIAL INTELLIGENCE; FORECASTING; MEDICAL COMPUTING; SURGERY;

CONTRIBUTING FACTOR; DEVELOPMENT AND TESTING; EARLY INTERVENTION; ELECTRONIC MEDICAL RECORD; EXACT CHANGE; INTRA-OPERATIVE; PRIOR KNOWLEDGE; RISK FACTORS;

LEARNING SYSTEMS;

ADVERSE EVENT; ARTICLE; ELECTRONIC MEDICAL RECORD; GENERAL ANESTHESIA; HUMAN; HYPOXEMIA; INTRAOPERATIVE PERIOD; MACHINE LEARNING; RISK ASSESSMENT; RISK FACTOR; ADULT; AGED; ANESTHESIOLOGIST; AREA UNDER THE CURVE; ELECTRONIC HEALTH RECORD; FEMALE; HYPOXIA; MALE; MIDDLE AGED; PSYCHOLOGY; RECEIVER OPERATING CHARACTERISTIC; SURGERY; VERY ELDERLY;

ADULT; AGED; AGED, 80 AND OVER; ANESTHESIA, GENERAL; ANESTHESIOLOGISTS; AREA UNDER CURVE; ELECTRONIC HEALTH RECORDS; FEMALE; HUMANS; HYPOXIA; MACHINE LEARNING; MALE; MIDDLE AGED; RISK FACTORS; ROC CURVE; SURGICAL PROCEDURES, OPERATIVE;

EID: 85054648327     PISSN: None     EISSN: 2157846X     Source Type: Journal    
DOI: 10.1038/s41551-018-0304-0     Document Type: Article

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