Deep learning and hybrid architectures for atypical and complex bone fracture diagnosis: a systematic review of performance and clinical validity
Artificial intelligence (AI) is reshaping fracture diagnosis in medical imaging. Despite these advances, accurately identifying atypical fractures (such as stress or pathological fractures) and complex fractures (including comminuted and pelvic fractures) remains a significant clinical challenge. This systematic review evaluates the current evidence on AI models, including advanced architectures, for detecting, classifying, and segmenting atypical and complex bone fractures in humans. A total of
Record details
Published: 10 August 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Healthcare
Retrieved: 11 August 2026
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How to cite this record
ethics.ai (10 August 2026), “Deep learning and hybrid architectures for atypical and complex bone fracture diagnosis: a systematic review of performance and clinical validity,” evidence record 18074, https://ethics.ai/record/18074 (originally published by Frontiers in Artificial Intelligence).
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