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Articles Published Processes
4/17/2025 8:25:07 AM | Browse: 12 | Download: 30
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Received |
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2024-11-25 13:37 |
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Peer-Review Started |
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2024-11-26 02:03 |
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To Make the First Decision |
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Return for Revision |
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2025-01-08 09:28 |
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Revised |
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2025-01-10 12:05 |
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Second Decision |
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2025-02-27 02:40 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-02-27 10:34 |
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Articles in Press |
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2025-02-27 10:34 |
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Publication Fee Transferred |
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2025-01-11 05:48 |
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Edit the Manuscript by Language Editor |
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2025-03-05 22:33 |
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Typeset the Manuscript |
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2025-04-10 03:18 |
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Publish the Manuscript Online |
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2025-04-17 08:25 |
| ISSN |
2218-5836 (online) |
| 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/ |
| Copyright |
The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Endocrinology & Metabolism |
| Manuscript Type |
Systematic Reviews |
| Article Title |
Accuracy of artificial intelligence in prediction of osteoporotic fractures in comparison to DXA and FRAX: A systematic review
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Mir Sadat-Ali, Bandar A Alzahrani, Turki S Alqahtani, Musaad A Alotaibi, Abdallah M Alhalafi, Ahmed A Alsousi and Abdullah M Alasiri |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Mir Sadat-Ali, Professor, Department of Orthopedic Surgery, Imam AbdulRahman Bin Faisal University and King Fahd Hospital of the University, Pobox 40071, AlKhobar 31952, Saudi Arabia. drsadat@hotmail.com |
| Key Words |
Artificial intelligence; Osteoporosis; Prediction; Fragility fractures |
| Core Tip |
Fragility fractures due to osteoporosis is a tremendous economic burden on health care and cause Pronounced morbidity and mortality. If a diagnosis of an impending fracture is made early then preventive measures can help in reducing the incidence of fractures. At present DXA and FRAX are two modalities which can predict fractures but they are not accurate. The emergence of artificial intelligence (AI) and its algorithms has changed this scenario completely. In this review we compared the three AI, DXA and FRAX and found that AI models are 99% accurate in predicting an impending fracture compared to DXA and FRAX which is about 70%. We believe and recommend that more studies on AI algorithms should be performed and the models should be made available universally. |
| Publish Date |
2025-04-17 08:25 |
| Citation |
<p>Sadat-Ali M, Alzahrani BA, Alqahtani TS, Alotaibi MA, Alhalafi AM, Alsousi AA, Alasiri AM. Accuracy of artificial intelligence in prediction of osteoporotic fractures in comparison to DXA and FRAX: A systematic review. <i>World J Orthop</i> 2025; 16(4): 103572</p> |
| URL |
https://www.wjgnet.com/2218-5836/full/v16/i4/103572.htm |
| DOI |
https://dx.doi.org/10.5312/wjo.v16.i4.103572 |
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