| For: | 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 with dual-energy X-ray absorptiometry and the Fracture Risk Assessment Tool: A systematic review. World J Orthop 2025; 16(4): 103572 [PMID: 40290609 DOI: 10.5312/wjo.v16.i4.103572] |
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| URL: | https://www.wjgnet.com/2218-5836/full/v16/i4/103572.htm |
| Number | Citing Articles |
| 1 |
Qipeng Wei, Zihao Liu, Xiaofeng Chen, Hao Li, Weijun Guo, Qingyan Huang, Jinxiang Zhan, Shiji Chen, Dongling Cai. Development and validation of an explainable machine learning model for predicting osteoporosis in patients with type 2 diabetes mellitus. Frontiers in Endocrinology 2025; 16 doi: 10.3389/fendo.2025.1611499
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| 2 |
Wisely Zhi-Tang Koay, Siow-Wee Chang, Raja Elina Ahmad, Tunku Kamarul. A scoping review of systematic reviews on artificial intelligence in orthopaedics. Journal of Orthopaedic Surgery 2026; 34(1) doi: 10.1177/10225536261424033
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| 3 |
Liukui Fan, Chenxi Huang, Qinglang Guo, Hao Jin, Peiwen Wang, Rongcheng Ouyang. Advanced Intelligent Computing Technology and Applications. Lecture Notes in Computer Science 2027; 16647 doi: 10.1007/978-981-92-3397-7_6
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| 4 |
Mahsa Shakeri, Seyyed Mohammad Hosseini, Nikolas Knowles, Forough Jamil, Mohammad Haghparast, Leili Darvish. The future of DXA: How AI is transforming bone health diagnostics. Journal of Microscopy 2026; doi: 10.1111/jmi.70140
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| 5 |
Jihao Cheng, Chuanjiang Liu, Mengyin Gu, Dongying Su, Jingyun Liao. Development and validation of a multimodal interpretable machine learning model for the identification of osteoporosis in patients with type 2 diabetes mellitus: a multicenter retrospective study. Frontiers in Endocrinology 2026; 17 doi: 10.3389/fendo.2026.1871923
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| 6 |
Qipeng Wei, Jinxiang Zhan, Xiaofeng Chen, Qingyan Huang, Hao Li, Weijun Guo, Zihao Liu, Shiji Chen, Dongling Cai. Development and validation of an interpretable machine learning model for osteoporosis prediction using routine blood tests: a retrospective cohort study. BMC Medical Informatics and Decision Making 2025; 25(1) doi: 10.1186/s12911-025-03292-1
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