Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical trial

Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical trial

BackgroundPredicting clinical improvement after hospital admission in patients with COVID-19 is crucial for effective resource allocation. Machine-learning tools can help identify patients likely to show clinical improvement based on real-world data. This study used two approaches—least absolute shr...

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Bibliographic Details
Main Authors: Caio César Souza Conceição, Camila Marinelli Martins, Mayck Medeiros Silva, Hugo Caire de Castro Faria Neto, Davide Chiumello, Patricia Rieken Macedo Rocco, Fernanda Ferreira Cruz, Pedro Leme Silva
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Medicine
Subjects:
COVID-19
biomarkers
machine learning
LASSO
CombiROC
clinical improvement
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1561980/full
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