Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion

• Main Authors: Alzubaidi L., AL-Dulaimi K., Salhi A., Alammar Z., Fadhel M.A., Albahri A.S., Alamoodi A.H., Albahri O.S., Hasan A.F., Bai J., Gilliland L., Peng J., Branni M., Shuker T., Cutbush K., Santamar�a J., Moreira C., Ouyang C., Duan Y., Manoufali M., Jomaa M., Gupta A., Abbosh A., Gu Y.
• Other Authors: 57195380379
• Format: Review
• Published: Elsevier B.V. 2025
• Subjects: Deep Learning; Humans; Orthopedics; Deep learning; Diagnosis; Fracture; Bone tumor; Fracture detection; Knowledge gaps; Orthopaedic applications; Orthopaedic surgeons; Orthopedic technology; Osteoarthritis; Trustworthy AI; Tumor diagnosis; arthroplasty; bone age determination; bone implant; bone tumor; deep learning; diagnosis; fairness; Food and Drug Administration; fracture; human; knowledge gap; MRI scanner; nuclear magnetic resonance imaging; orthopedic surgeon; orthopedics; osteoarthritis; prediction; review; soft tissue disease; therapy; treatment planning; trustworthiness; tumor diagnosis; Web of Science; procedures

Deep learning (DL) in orthopaedics has gained significant attention in recent years. Previous studies have shown that DL can be applied to a wide variety of orthopaedic tasks, including fracture detection, bone tumour diagnosis, implant recognition, and evaluation of osteoarthritis severity. The uti...