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Deep learning for radiographic differentiation between lateral malleolar avulsion fractures and subfibular ossicles
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DOI：10.1016/j.isci.2026.116414.png)
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Abstract
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• A two-stage DL pipeline detects and classifies LMAFs and SFOs on ankle radiographs • MobileNetV2 achieved an external-test AUC of 0.887, outperforming comparator models • AI assistance significantly improved radiologists’ diagnostic accuracy for LMAF versus SFO • Grad-CAMs showed the model focused on clinically relevant fracture or ossicle features
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health sciences
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