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©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Orthop. Apr 18, 2025; 16(4): 103572
Published online Apr 18, 2025. doi: 10.5312/wjo.v16.i4.103572
Published online Apr 18, 2025. doi: 10.5312/wjo.v16.i4.103572
Accuracy of artificial intelligence in prediction of osteoporotic fractures in comparison with dual-energy X-ray absorptiometry and the Fracture Risk Assessment Tool: A systematic review
Mir Sadat-Ali, Department of Orthopedic Surgery, Haifa Medical Complex, Al Khobar 32424, Saudi Arabia
Bandar A Alzahrani, Musaad A Alotaibi, Abdallah M Alhalafi, Ahmed A Alsousi, Department of Orthopedics, College of Medicine, Imam Abdulrahman bin Faisal University, Dammam 34212, Saudi Arabia
Turki S Alqahtani, Department of Orthopaedic Surgery, King Fahd Military Medical Complex, Dhahran, Saudi Arabia
Abdullah M Alasiri, Department of Orthopaedic Surgery, Security Forces Hospital, Dammam, Saudi Arabia
Author contributions: Sadat-Ali M contributed to the conceptualization, methodology, original draft preparation, and reviewing and editing; Alzahrani BA and Alasiri AM contributed to the data collection and visualization curation; Alqahtani TS contributed to the investigation, data review, visualization, and investigation; Alotaibi MA and Alsousi AA contributed to the supervision software and validation; Alhalafi AM contributed to the literature review, writing, and editing.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
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: Mir Sadat-Ali, Professor, Department of Orthopedic Surgery, Haifa Medical Complex, 7200 King Khalid Road, Al Khobar 32424, Saudi Arabia.
Received: November 25, 2024
Revised: January 10, 2025
Accepted: February 27, 2025
Published online: April 18, 2025
Processing time: 145 Days and 2 Hours
Revised: January 10, 2025
Accepted: February 27, 2025
Published online: April 18, 2025
Processing time: 145 Days and 2 Hours
Core Tip
Core Tip: Fragility fractures due to osteoporosis are a tremendous economic burden and cause pronounced morbidity and mortality. Early diagnosis allows the initiation of preventive measures to reduce the incidence of fractures. Dual-energy X-ray absorptiometry (DXA) and the Fracture Risk Assessment Tool (FRAX) are two inaccurate modalities used to predict fractures. The emergence of artificial intelligence (AI) has changed this scenario completely. We compared AI, DXA, and FRAX and found that AI models are 99% accurate in predicting an impending fracture compared with DXA and FRAX, which are about 70%. More studies on AI should be performed before made universally available.