The Bone & Joint Journal

The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an effective diagnostic tool for DDH. Here, we aimed to develop an anteroposterior pelvic radiograph deep learning system for diagnosing DDH in children and analyze the feasibility of its application. In total, 10,219 anteroposterior pelvic radiographs were retrospectively collected from April 2014 to December 2018. Radiographs were grouped according to age and into'dislocation' (dislocation and subluxation) and'non-dislocation' (normal cases and those with dysplasia of the acetabulum) groups based on clinical diagnosis.