Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learning.

Shawwa, Khaled; Ghosh, Erina; Lanius, Stephanie; Schwager, Emma; Eshelman, Larry; Kashani, Kianoush B

Shawwa, Khaled; Ghosh, Erina; Lanius, Stephanie; Schwager, Emma; Eshelman, Larry; Kashani, Kianoush B.

Afiliação

Shawwa K; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA.
Ghosh E; Philips Research North America, Cambridge, MA, USA.
Lanius S; Philips Research North America, Cambridge, MA, USA.
Schwager E; Philips Research North America, Cambridge, MA, USA.
Eshelman L; Philips Research North America, Cambridge, MA, USA.
Kashani KB; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA.

Clin Kidney J ; 14(5): 1428-1435, 2021 May.

Article em En | MEDLINE | ID: mdl-33959271

Palavras-chave

acute kidney injury; critical care; intensive care unit; machine learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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