Introduction In orthopaedic surgery, integrating Artificial Intelligence (AI) into diagnostic imaging is a significant breakthrough. This application, powered by advanced algorithms, enhances radiological accuracy in the identification of musculoskeletal conditions. This review will explore the benefits and limitations of the use of AI for diagnostic imaging in orthopaedic surgery.

Methods Systematic searches were conducted on the Ovid MEDLINE and PubMed electronic databases to identify relevant studies for this review. The literature search utilised key terms and a strict inclusion and exclusion criteria was applied. The final studies underwent critical appraisal using the CASP tool.

Results AI algorithms are able to analyse radiographic images with remarkable precision, identifying anomalies such as fractures and diagnosing conditions including meniscus injury and osteoarthritis. AI’s ability to process vast datasets enables early detection, facilitating timely intervention. AI systems can operate tirelessly, optimising workflow efficiency. Limitations include algorithmic biases, emphasising importance of representative datasets, and challenges with rare or complex cases that require human expertise and clinical judgment.

Conclusion Balancing technological integration and human input remains crucial to maximise AI benefits. Ongoing research is essential for unlocking the full potential of AI, ensuring advancements and improved patient care in orthopaedic surgery.