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Machine learning models for predicting in-hospital mortality in patient with sepsis: Analysis of vital sign dynamics

PURPOSE: To build machine learning models for predicting the risk of in-hospital death in patients with sepsis within 48 h, using only dynamic changes in the patient's vital signs. METHODS: This retrospective observational cohort study enrolled septic patients from five emergency departments (E...

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Detalles Bibliográficos
Autores principales:	Cheng, Chi-Yung, Kung, Chia-Te, Chen, Fu-Cheng, Chiu, I-Min, Lin, Chun-Hung Richard, Chu, Chun-Chieh, Kung, Chien Feng, Su, Chih-Min
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Medicine
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9631306/ https://www.ncbi.nlm.nih.gov/pubmed/36341257 http://dx.doi.org/10.3389/fmed.2022.964667

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