Current applications of deep learning in vertebral fracture diagnosis
- PMID: 40764417
- DOI: 10.1007/s00198-025-07604-z
Current applications of deep learning in vertebral fracture diagnosis
Abstract
Deep learning is a machine learning method that mimics neural networks to build decision-making models. Recent advances in computing power and algorithms have enhanced deep learning's potential for vertebral fracture diagnosis in medical imaging. The application of deep learning in vertebral fracture diagnosis, including the identification of vertebrae and classification of vertebral fracture types, might significantly reduce the workload of radiologists and orthopedic surgeons as well as greatly improve the accuracy of vertebral fracture diagnosis. In this narrative review, we will summarize the application of deep learning models in the diagnosis of vertebral fractures.
Keywords: Deep learning; Diagnosis; Vertebral fracture.
© 2025. The Author(s), under exclusive licence to the International Osteoporosis Foundation and the Bone Health and Osteoporosis Foundation.
Conflict of interest statement
Declarations. Conflicts of interest: None.
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