Personalizing anesthetic management in trauma patients using machine learning
This review aimed to report the current applications and future perspectives of artificial intelligence in the anesthetic management of severely injured patients. It also emphasizes its potential to enhance decision-making, personalize care, and ultimately improve patients' outcomes in trauma anesthesia.
Authors
- A. Everette James (ORCID: https://orcid.org/0000-0002-6174-6696)
- Jean-Denis Moyer
Institutions
- Sorbonne Université (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Centre Hospitalier Universitaire de Caen Normandie (FR)
- Pitié-Salpêtrière Hospital (FR)
- Université de Caen Normandie (FR)
Publication Details
- Journal
- Current Opinion in Anaesthesiology
- Published
- 2026-03-23
- DOI
- https://doi.org/10.1097/aco.0000000000001637
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00