Development and validation of a machine learning model for real-time prediction of invasive mechanical ventilation weaning readiness
This study presents three ML models for real-time prediction of IMV weaning readiness, offering a promising approach to enhance clinical decision-making and optimize patient care.
Authors
- Vittorio Scaravilli (ORCID: https://orcid.org/0000-0003-0877-7626)
- Andrea Ancona (ORCID: https://orcid.org/0000-0001-5114-7502)
- Lucrezia Rovati (ORCID: https://orcid.org/0000-0003-1222-9825)
- Francesca Alfieri (ORCID: https://orcid.org/0000-0003-4337-4523)
- Simone Zappalá (ORCID: https://orcid.org/0000-0002-8221-2626)
- Marco Bosone (ORCID: https://orcid.org/0009-0006-6347-1135)
- Giacomo Grasselli
Institutions
- University of Milan (IT)
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT)
- Azienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda (IT)
- Department of Medical Sciences (BY)
Publication Details
- Journal
- Journal of Critical Care
- Published
- 2025-05-26
- DOI
- https://doi.org/10.1016/j.jcrc.2025.155105
- Citations
- 1
- Primary Topic
- Respiratory Support and Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 1.52
Funders
- Ministero della Salute