Abstract: Developmental dysplasia of the hip (DDH) is a common orthopedic disorder characterized by insufficient acetabular development and inadequate coverage of the femoral head,leading to joint instability,chronic pain,and early osteoarthritis,which severely impacts patients’ quality of life.Traditional diagnostic and treatment methods rely on imaging and clinical experience,and are limited by high subjectivity,inadequate individualized therapy,and delayed postoperative rehabilitation monitoring.In recent years,artificial intelligence (AI) has made breakthroughs in medical image processing,machine learning,and robot-assisted surgery.By leveraging deep learning,AI enables automatic segmentation and quantitative analysis of multimodal images,effectively enhancing diagnostic accuracy and the scientific basis for treatment decision-making.Meanwhile,3D reconstruction,virtual surgical simulation,and remote rehabilitation monitoring provide robust support for surgical planning and dynamic management.This review summarizes the progress and challenges of applying AI in the diagnosis,treatment decision-making,surgical planning,and rehabilitation management of DDH,and outlines future directions for technological innovation and clinical practice optimization.

Key words: developmental dysplasia of the hip, artificial intelligence, medical image processing, surgical planning, rehabilitation management