Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.

Hsu, Chien-Ning; Liu, Chien-Liang; Tain, You-Lin; Kuo, Chin-Yu; Lin, Yun-Chun

Hsu, Chien-Ning; Liu, Chien-Liang; Tain, You-Lin; Kuo, Chin-Yu; Lin, Yun-Chun.

Afiliación

Hsu CN; Department of Pharmacy, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan.
Liu CL; School of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan.
Tain YL; Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan.
Kuo CY; Division of Pediatric Nephrology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung Medical University, Kaohsiung, Taiwan.
Lin YC; Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan.

J Med Internet Res ; 22(8): e16903, 2020 08 04.

Article en En | MEDLINE | ID: mdl-32749223

Asunto(s)

Lesión Renal Aguda/epidemiología; Infecciones Comunitarias Adquiridas/epidemiología; Aprendizaje Automático/normas; Medición de Riesgo/métodos; Anciano; Estudios de Casos y Controles; Estudios de Cohortes; Registros Electrónicos de Salud; Femenino; Hospitalización; Humanos; Masculino; Persona de Mediana Edad

Palabras clave

clinical decision support system; community-acquired acute kidney injury (CA-AKI); feature selection with extreme gradient boost (XGBoost); hospitalization; least absolute shrinkage and selection operator (LASSO); machine learning; risk prediction; treatment decision making

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Infecciones Comunitarias Adquiridas / Medición de Riesgo / Lesión Renal Aguda / Aprendizaje Automático Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Taiwán

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