Development of a diagnostic support system for distal humerus fracture using artificial intelligence

ConclusionThe developed deep learning –based diagnostic support system shows potential for accurately diagnosing distal humerus fractures using AP and lateral elbow radiographs. The model’s specificity and PPV indicate its ability to mark out occult lesions and has a high false positive rate. Further research and validation are nece ssary to improve the sensitivity and diagnostic accuracy of the model for practical clinical implementation.
Source: International Orthopaedics - Category: Orthopaedics Source Type: research