A machine-learning regional clustering approach to understand ventilator-induced lung injury: a proof-of-concept experimental study

A machine-learning regional clustering approach to understand ventilator-induced lung injury: a proof-of-concept experimental study

Abstract Background The spatiotemporal progression and patterns of tissue deformation in ventilator-induced lung injury (VILI) remain understudied. Our aim was to identify lung clusters based on their regional mechanical behavior over space and time in lungs subjected to VILI using machine-learning...

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Bibliographic Details
Main Authors: Pablo Cruces, Jaime Retamal, Andrés Damián, Graciela Lago, Fernanda Blasina, Vanessa Oviedo, Tania Medina, Agustín Pérez, Lucía Vaamonde, Rosina Dapueto, Sebastian González-Dambrauskas, Alberto Serra, Nicolas Monteverde-Fernandez, Mauro Namías, Javier Martínez, Daniel E. Hurtado
Format: Article
Language:English
Published: SpringerOpen 2024-07-01
Series:Intensive Care Medicine Experimental
Subjects:
Mechanical ventilation
Ventilator-induced lung injury
Lung strain
Computed tomography
Diagnostic imaging
Online Access:https://doi.org/10.1186/s40635-024-00641-8

Internet

https://doi.org/10.1186/s40635-024-00641-8

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