Interpretable machine learning models for predicting in-hospital death in patients in the intensive care unit with cerebral infarction.

Ouyang, Yang; Cheng, Meng; He, Bingqing; Zhang, Fengjuan; Ouyang, Wen; Zhao, Jianwu; Qu, Yang

Ouyang, Yang; Cheng, Meng; He, Bingqing; Zhang, Fengjuan; Ouyang, Wen; Zhao, Jianwu; Qu, Yang.

Afiliación

Ouyang Y; Department of Orthopedics, The Second Hospital of Jilin University, 218 Ziqiang Street, Changchun 130041, China.
Cheng M; Department of Orthopedics, The Second Hospital of Jilin University, 218 Ziqiang Street, Changchun 130041, China.
He B; Department of Neurology, The Second Hospital of Jilin University, 218 Ziqiang Street, Changchun 130041, China.
Zhang F; Department of Neurology, The Second Hospital of Jilin University, 218 Ziqiang Street, Changchun 130041, China.
Ouyang W; Department of Endocrinology, First People's Hospital of Changde City, 818 renmin Street, Changde 415000, China.
Zhao J; Department of Orthopedics, The Second Hospital of Jilin University, 218 Ziqiang Street, Changchun 130041, China. Electronic address: jianwu@jlu.edu.cn.
Qu Y; Department of Orthopedics, The Second Hospital of Jilin University, 218 Ziqiang Street, Changchun 130041, China. Electronic address: quy@jlu.edu.cn.

Comput Methods Programs Biomed ; 231: 107431, 2023 Apr.

Article en En | MEDLINE | ID: mdl-36827826

Asunto(s)

Cuidados Críticos; Unidades de Cuidados Intensivos; Humanos; Mortalidad Hospitalaria; Infarto Cerebral; Aprendizaje Automático

Palabras clave

Cerebral infarction; Intensive care unit (ICU); Machine learning (ML); Mortality; Prediction model

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Cuidados Críticos / Unidades de Cuidados Intensivos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Methods Programs Biomed Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: China

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