Identifying Predictors of COVID-19 Mortality Using Machine Learning.

Wan, Tsz-Kin; Huang, Rui-Xuan; Tulu, Thomas Wetere; Liu, Jun-Dong; Vodencarevic, Asmir; Wong, Chi-Wah; Chan, Kei-Hang Katie

Wan, Tsz-Kin; Huang, Rui-Xuan; Tulu, Thomas Wetere; Liu, Jun-Dong; Vodencarevic, Asmir; Wong, Chi-Wah; Chan, Kei-Hang Katie.

Afiliación

Wan TK; Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China.
Huang RX; Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China.
Tulu TW; Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China.
Liu JD; Computational Data Science Program, Addis Ababa University, Addis Ababa 1176, Ethiopia.
Vodencarevic A; Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China.
Wong CW; Novartis Oncology, Novartis Pharma GmbH, 90429 Nuremberg, Germany.
Chan KK; Department of Applied AI and Data Science, City of Hope, Duarte, CA 91010, USA.

Life (Basel) ; 12(4)2022 Apr 06.

Article en En | MEDLINE | ID: mdl-35455038

Palabras clave

COVID-19; COVID-19 mortality; machine learning model; mortality predictors; prediction model

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Life (Basel) Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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