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)

Frontiers in Pediatrics

Robert A. Reed¹  Jennifer Zeitlin¹  Babak Khoshnood¹  Héloïse Torchin²  Pierre-Henri Jarreau²  Véronique Pierrat³  Pierre-Yves Ancel⁴  Andrei S. Morgan⁵ 

[1] Université de Paris, Epidemiology and Statistics Research Center/CRESS, INSERM, INRA, Paris, France;Université de Paris, Epidemiology and Statistics Research Center/CRESS, INSERM, INRA, Paris, France;APHP.5, Service de Médecine et Réanimation Néonatales de Port-Royal, Paris, France;Université de Paris, Epidemiology and Statistics Research Center/CRESS, INSERM, INRA, Paris, France;CHU Lille, Department of Neonatal Medicine, Jeanne de Flandre Lille, France;Université de Paris, Epidemiology and Statistics Research Center/CRESS, INSERM, INRA, Paris, France;Clinical Research Unit, Center for Clinical Investigation P1419, APHP.5, Paris, France;Université de Paris, Epidemiology and Statistics Research Center/CRESS, INSERM, INRA, Paris, France;Elizabeth Garrett Anderson Institute for Womens' Health, University College London (UCL), London, United Kingdom;SAMU 93, SMUR Pédiatrique, CHI André Gregoire, Groupe Hospitalier Universitaire Paris Seine-Saint-Denis, Assistance Publique des Hôpitaux de Paris, Paris, France;

关键词: neonatology;    rehospitalisation;    prediction;    machine-learning;    epidemiology;   

DOI  :  10.3389/fped.2020.585868

来源: Frontiers

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CC BY