Academic Journal
AI algorithms for accurate prediction of osteoporotic fractures in patients with diabetes: an up-to-date review
| Title: | AI algorithms for accurate prediction of osteoporotic fractures in patients with diabetes: an up-to-date review |
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| Authors: | Zeting Li, Wen Zhao, Xiahong Lin, Fangping Li |
| Source: | Journal of Orthopaedic Surgery and Research, Vol 18, Iss 1, Pp 1-11 (2023) |
| Publisher Information: | BMC, 2023. |
| Publication Year: | 2023 |
| Collection: | LCC:Orthopedic surgery LCC:Diseases of the musculoskeletal system |
| Subject Terms: | Osteoporotic fracture, Artificial intelligence, Fracture prediction, Diabetes, Orthopedic surgery, RD701-811, Diseases of the musculoskeletal system, RC925-935 |
| More Details: | Abstract Osteoporotic fractures impose a substantial burden on patients with diabetes due to their unique characteristics in bone metabolism, limiting the efficacy of conventional fracture prediction tools. Artificial intelligence (AI) algorithms have shown great promise in predicting osteoporotic fractures. This review aims to evaluate the application of traditional fracture prediction tools (FRAX, QFracture, and Garvan FRC) in patients with diabetes and osteoporosis, review AI-based fracture prediction achievements, and assess the potential efficiency of AI algorithms in this population. This comprehensive literature search was conducted in Pubmed and Web of Science. We found that conventional prediction tools exhibit limited accuracy in predicting fractures in patients with diabetes and osteoporosis due to their distinct bone metabolism characteristics. Conversely, AI algorithms show remarkable potential in enhancing predictive precision and improving patient outcomes. However, the utilization of AI algorithms for predicting osteoporotic fractures in diabetic patients is still in its nascent phase, further research is required to validate their efficacy and assess the potential advantages of their application in clinical practice. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1749-799X |
| Relation: | https://doaj.org/toc/1749-799X |
| DOI: | 10.1186/s13018-023-04446-5 |
| Access URL: | https://doaj.org/article/7c54411fdd99404cae378ae8ee0b0919 |
| Accession Number: | edsdoj.7c54411fdd99404cae378ae8ee0b0919 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 1749799X |
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| DOI: | 10.1186/s13018-023-04446-5 |
| Published in: | Journal of Orthopaedic Surgery and Research |
| Language: | English |