Machine Learning Approaches to Predict In-Hospital Mortality among Neonates with Clinically Suspected Sepsis in the Neonatal Intensive Care Unit

Background: preterm and critically ill neonates often experience clinically suspected sepsis during their prolonged hospitalization in the neonatal intensive care unit (NICU), which can be the initial sign of final adverse outcomes. Therefore, we aimed to utilize machine learning approaches to predi...

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Detalles Bibliográficos
Autores principales: Hsu, Jen-Fu, Chang, Ying-Feng, Cheng, Hui-Jun, Yang, Chi, Lin, Chun-Yuan, Chu, Shih-Ming, Huang, Hsuan-Rong, Chiang, Ming-Chou, Wang, Hsiao-Chin, Tsai, Ming-Horng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8400295/
https://www.ncbi.nlm.nih.gov/pubmed/34442338
http://dx.doi.org/10.3390/jpm11080695

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8400295/
https://www.ncbi.nlm.nih.gov/pubmed/34442338
http://dx.doi.org/10.3390/jpm11080695

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