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

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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Bibliographic Details
Main Authors: Jen-Fu Hsu, Ying-Feng Chang, Hui-Jun Cheng, Chi Yang, Chun-Yuan Lin, Shih-Ming Chu, Hsuan-Rong Huang, Ming-Chou Chiang, Hsiao-Chin Wang, Ming-Horng Tsai
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Journal of Personalized Medicine
Subjects:
neonatal mortality
artificial intelligence
big data analysis
early prediction
machine learning
Online Access:https://www.mdpi.com/2075-4426/11/8/695

Internet

https://www.mdpi.com/2075-4426/11/8/695

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