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World J Clin Cases. Jun 26, 2023; 11(18): 4231-4240
Published online Jun 26, 2023. doi: 10.12998/wjcc.v11.i18.4231
Application of artificial intelligence in trauma orthopedics: Limitation and prospects
Maryam Salimi, Joshua A Parry, Raha Shahrokhi, Seyedarad Mosalamiaghili
Maryam Salimi, Joshua A Parry, Department of Orthopaedic Surgery, Denver Health Medical Center, Denver, CO 80215, United States
Raha Shahrokhi, Seyedarad Mosalamiaghili, Student Research Committee, Shiraz University of Medical Sciences, Shiraz 7138433608, Iran
Author contributions: Salimi M designed the study; Parry JA edited the manuscript significantly; Shahrokhi R and Mosalamiaghili S reviewed literature and provided the input in writing the paper.
Conflict-of-interest statement: There is no conflict of interest associated with any of the senior authors or other coauthors who contributed their efforts to this manuscript.
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: Seyedarad Mosalamiaghili, MD, Researcher, Student Research Committee, Shiraz University of Medical Sciences, Zand Avenue, Shiraz 7138433608, Iran. aradmosalami@gmail.com
Received: January 26, 2023
Peer-review started: January 26, 2023
First decision: April 10, 2023
Revised: April 23, 2023
Accepted: May 8, 2023
Article in press: May 8, 2023
Published online: June 26, 2023
Core Tip

Core Tip: Machine learning is currently applied to image-screening assistance, predictive analytics, and intraoperative robotics, specifically in the trauma orthopedics field. Artificial intelligence can be used in the emergency department of trauma centers as a screening tool and aid to orthopedists, helping them improve their sensitivity and specificity and help shorten their diagnosis time. In real-life practice, orthopedic surgeons consider various factors when making a prediction; that is why machine learning-based predictive models include features such as history and physical exam data, along with imaging results. Artificial intelligence application may be able to identify such patterns and increase the chance of optimum results.