Artificial Intelligence in Orthopaedic Research: A Technical Report on Opportunities and Pitfalls

Artificial intelligence is transforming the landscape of orthopaedic research, offering tools that enhance data analysis, improve diagnostic workflows, and support personalized patient care. In recent years, AI applications in orthopaedics have expanded significantly, ranging from imaging-based fracture detection and musculoskeletal tumor classification to surgical planning, implant identification, and biomechanical gait analysis. Additionally, AI is being used in research-centric tasks, including outcome prediction modeling, literature screening, and preliminary manuscript drafting. This technical report presents a narrative technical review synthesizing emerging applications of AI within orthopaedic research based on recent PubMed-indexed studies from the past five years. We explore how machine learning and deep learning algorithms are being developed, validated, and deployed across various research domains. The report highlights the tangible benefits of AI, such as increased efficiency, diagnostic precision, and reproducibility of analysis. However, it also addresses the significant pitfalls, including reliance on limited or biased datasets, lack of model transparency, and unresolved ethical challenges. Of particular concern is the use of generative AI tools in scientific writing, which, while promising, raises questions about originality, accuracy, and research integrity. Overall, AI is poised to support, not replace, orthopaedic researchers. Successful integration will require robust validation, ethical safeguards, and continued collaboration between data scientists and clinical experts.