Integrating artificial intelligence into orthopedics: Opportunities, challenges, and future directions

Abstract

Purpose: Artificial intelligence (AI) is transforming orthopedics by improving diagnostic accuracy, optimizing surgical planning, and personalizing treatment approaches. This review evaluates the applications of AI in orthopedics, focusing on its impact on patient care, the efficacy of AI methodologies, and challenges in integrating these technologies into clinical practice.

Methods: A comprehensive literature search was conducted across PubMed, Scopus, and Google Scholar for articles published up to 28^th February 2025. Inclusion criteria included studies addressing AI applications in orthopedics, while non-peer-reviewed and non-English publications were excluded. Data extraction focused on AI technologies, applications, outcomes, and the advantages or limitations of AI integration.

Results: Findings demonstrate AI's effectiveness in areas such as fracture detection and treatment planning, mainly through machine learning and deep learning. AI has improved outcomes in joint reconstruction, spine surgery, and rehabilitation. However, challenges such as data standardization and clinical validation remain.

Conclusion: The review highlights AI's potential to revolutionize orthopedic practice, emphasizing the need for ongoing research to overcome barriers to adoption. Future directions should prioritize multi-center clinical trials, enhanced data protocols, and stakeholder collaboration to ensure ethical and effective AI implementation, ultimately improving patient outcomes and care delivery.

Keywords: Artificial intelligence; Data mining; Machine learning; Orthopedics; Robotics.