Machine learning-based identification of efficient and restrictive physiological subphenotypes in acute respiratory distress syndrome

Machine learning-based identification of efficient and restrictive physiological subphenotypes in acute respiratory distress syndrome

Abstract Introduction Acute respiratory distress syndrome (ARDS) is a severe condition with high morbidity and mortality, characterized by significant clinical heterogeneity. This heterogeneity complicates treatment selection and patient inclusion in clinical trials. Therefore, the objective of this...

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Bibliographic Details
Main Authors: Gabriela Meza-Fuentes, Iris Delgado, Mario Barbé, Ignacio Sánchez-Barraza, Mauricio A. Retamal, René López
Format: Article
Language:English
Published: SpringerOpen 2025-03-01
Series:Intensive Care Medicine Experimental
Subjects:
Acute respiratory distress syndrome
Subphenotypes
Artificial intelligence
Personalized medicine
Online Access:https://doi.org/10.1186/s40635-025-00737-9

Internet

https://doi.org/10.1186/s40635-025-00737-9

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