Marino L, Bilotta F. Artificial intelligence in traumatic brain injury: Brain imaging analysis and outcome prediction: A mini review. World J Crit Care Med 2025; 14(3): 107611 [DOI: 10.5492/wjccm.v14.i3.107611]
Corresponding Author of This Article
Federico Bilotta, MD, PhD, Professor, Department of Anesthesiology, Critical Care and Pain Medicine, University of Rome “La Sapienza”, Piazzale Aldo Moro 5, Rome 00185, Italy. federico.bilotta@uniroma1.it
Research Domain of This Article
Anesthesiology
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Crit Care Med. Sep 9, 2025; 14(3): 107611 Published online Sep 9, 2025. doi: 10.5492/wjccm.v14.i3.107611
Artificial intelligence in traumatic brain injury: Brain imaging analysis and outcome prediction: A mini review
Luca Marino, Federico Bilotta
Luca Marino, Department of Mechanical and Aerospace Engineering, “Sapienza” University of Rome, Rome 00185, Italy
Federico Bilotta, Department of Anesthesiology, Critical Care and Pain Medicine, University of Rome “La Sapienza”, Rome 00185, Italy
Author contributions: Luca M performed writing the paper; Federico B designed the outline and supervised the writing of the paper
Conflict-of-interest statement: All authors declare that they have no competing interests.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Federico Bilotta, MD, PhD, Professor, Department of Anesthesiology, Critical Care and Pain Medicine, University of Rome “La Sapienza”, Piazzale Aldo Moro 5, Rome 00185, Italy. federico.bilotta@uniroma1.it
Received: March 27, 2025 Revised: April 15, 2025 Accepted: May 24, 2025 Published online: September 9, 2025 Processing time: 114 Days and 1.3 Hours
Abstract
Integration of artificial intelligence increases in all aspects of human life, particularly in healthcare systems. Traumatic brain injury is a significant cause of mortality and long-term disability, with an important impact on the socio-economic system of healthcare. The role of artificial intelligence in imaging and outcome prediction for traumatic brain injury patients is reviewed with a particular emphasis to the characteristics of machine and deep learning methods. Evidence of potential improvement in the clinical practice in discussed.
Core Tip: Several reviews in the literature contributed to the role of Artificial Intelligence (AI) in medicine. However, this mini-review focuses of the potential role of AI in imaging analysis and outcome prediction of traumatic brain injury patients. Evidence of the latest results obtained with different AI-based technologies, in particular Machine learning and Deep learning algorithms, are provided.
