Prediction and detection models for acute kidney injury in hospitalized older adults

BMC Medical Informatics and Decision Making

Volumn 16, Issue 1, 2016, Pages

  Kate, Rohit J ^a   Perez, Ruth M ^b   Mazumdar, Debesh ^c   Pasupathy, Kalyan S ^d   Nilakantan, Vani ^b  

^a UNIVERSITY OF WISCONSIN MILWAUKEE   (United States)

^b Aurora Health Care   (United States)

^c Milwaukee Kidney Associates   (United States)

^d MAYO CLINIC   (United States)

Author keywords

Acute kidney injury (AKI); Detection; Elderly; Machine learning; Modeling; Prediction

Indexed keywords

ACUTE KIDNEY INJURY; AGED; FEMALE; HOSPITALIZATION; HUMAN; MACHINE LEARNING; MALE; MIDDLE AGED; PROGNOSIS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; THEORETICAL MODEL; VERY ELDERLY;

ACUTE KIDNEY INJURY; AGED; AGED, 80 AND OVER; FEMALE; HOSPITALIZATION; HUMANS; MACHINE LEARNING; MALE; MIDDLE AGED; MODELS, STATISTICAL; MODELS, THEORETICAL; PROGNOSIS;

EID: 85007609237     PISSN: None     EISSN: 14726947     Source Type: Journal    
DOI: 10.1186/s12911-016-0277-4     Document Type: Article

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