Clinical outcome prediction using observational supervision with electronic health records and audit logs.

Bhaskhar, Nandita; Ip, Wui; Chen, Jonathan H; Rubin, Daniel L

Bhaskhar, Nandita; Ip, Wui; Chen, Jonathan H; Rubin, Daniel L.

Afiliación

Bhaskhar N; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA. Electronic address: nanbhas@stanford.edu.
Ip W; Department of Pediatrics, Stanford School of Medicine, Palo Alto, CA 94305, USA.
Chen JH; Center for Biomedical Informatics Research, Stanford University, Stanford, CA 94305, USA; Division of Hospital Medicine, Stanford School of Medicine, Palo Alto, CA 94305, USA; Clinical Excellence Research Center, Stanford School of Medicine, Palo Alto, CA 94305, USA.
Rubin DL; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Department of Radiology, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Stanford School of Medicine, Palo Alto, CA 94305, USA.

J Biomed Inform ; 147: 104522, 2023 11.

Article en En | MEDLINE | ID: mdl-37827476

Asunto(s)

Lesión Renal Aguda; Accidente Cerebrovascular; Humanos; Registros Electrónicos de Salud; Hospitalización; Pronóstico

Palabras clave

30-day hospital readmission; Acute ischemic stroke; Acute kidney injury (AKI); Audit logs; Electronic health records (EHR); Major adverse kidney event (MAKE); Observational supervision

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Accidente Cerebrovascular / Lesión Renal Aguda Límite: Humans Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos

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