Artificial intelligence for detecting subtle paediatric tibial fractures in children under three years: An analysis of YOLO architectures with convolutional Block attention.

YOLO-based models show potential for detecting subtle tibial fractures in infants and toddlers, and Convolutional Block Attention Module further enhances performance in difficult cases.

Larger multicentre datasets are needed to strengthen generalisability.

IMPLICATIONS FOR PRACTICE: AI-assisted detection could support radiologists in suspected non-accidental injury, reduce missed fractures, and improve diagnostic pathways, particularly in settings without specialist paediatric radiology expertise.