The role of artificial intelligence in orthopedic surgery: Current applications and future perspectives—A systematic review of the literature

Abstract

OBJECTIVE: This systematic review aimed to evaluate the current applications, clinical outcomes, and limitations of artificial intelligence (AI) in orthopaedic surgery across diagnostics, pre-surgical planning, robotic-assisted interventions, and postoperative care. METHODS: A comprehensive search across PubMed, Scopus, Web of Science, and Google Scholar (2018-2025) identified 125 studies, of which 47 met inclusion criteria. RESULTS: AI-based imaging tools demonstrated high diagnostic accuracy, with some models achieving sensitivities up to 98.2% and area under the curve (AUC) values exceeding 0.95 in fracture detection and musculoskeletal anomaly identification. In pre-surgical planning, AI-driven 3D modelling improved implant conformity (acetabular cup 90.9% vs. 72.2%; femoral stem 87.3% vs. 66.7%) and enhanced surgical risk prediction (AUC>0.85 for complications). Robotic-assisted surgeries incorporating AI-guided planning improved implant alignment and procedural consistency, although long-term functional outcomes remained inconclusive. In the postoperative setting, 17 of 18 trials using wearable or app-based interventions reported improved functional recovery, patient satisfaction, and adherence. CONCLUSION: AI is playing an increasingly important role in orthopaedic surgery, offering promising improvements in diagnostic accuracy, surgical precision, and rehabilitation support. However, challenges remain regarding external validation, algorithmic bias, and regulatory frameworks.

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