Machine-Learning vs. Expert-Opinion Driven Logistic Regression Modelling for Predicting 30-Day Unplanned Rehospitalisation in Preterm Babies: A Prospective, Population-Based Study (EPIPAGE 2)

Machine-Learning vs. Expert-Opinion Driven Logistic Regression Modelling for Predicting 30-Day Unplanned Rehospitalisation in Preterm Babies: A Prospective, Population-Based Study (EPIPAGE 2)

Introduction: Preterm babies are a vulnerable population that experience significant short and long-term morbidity. Rehospitalisations constitute an important, potentially modifiable adverse event in this population. Improving the ability of clinicians to identify those patients at the greatest risk...

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Bibliographic Details
Main Authors: Robert A. Reed, Andrei S. Morgan, Jennifer Zeitlin, Pierre-Henri Jarreau, Héloïse Torchin, Véronique Pierrat, Pierre-Yves Ancel, Babak Khoshnood
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Pediatrics
Subjects:
neonatology
rehospitalisation
prediction
machine-learning
epidemiology
Online Access:https://www.frontiersin.org/articles/10.3389/fped.2020.585868/full

Internet

https://www.frontiersin.org/articles/10.3389/fped.2020.585868/full

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