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Rad Croatian Academy of Sciences and Arts. Medical sciences : Medical Sciences, Vol. 570X No. 74-75, 2026.

Review article

Artificial Intelligence in Orthopedics: Clinical Applications, Challenges, and Opportunities

Ivo Dumić-Čule
Denis Tršek
Marko Pećina

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Abstract

This review provides a comprehensive overview of the rapidly expanding role of artificial intelligence (AI) in orthopedic practice, highlighting its applications across prevention, imaging, surgery, and rehabilitation. AI encompasses technologies such as machine learning and deep learning, which enable the analysis of complex datasets and support predictive, personalized medical approaches.
In prevention and early disease detection, AI-driven models utilizing wearable sensors and biomechanical data demonstrate strong potential in identifying injury risk and early pathological changes before clinical symptoms emerge. In musculoskeletal imaging, AI significantly enhances diagnostic accuracy in fracture detection, osteoarthritis assessment, and tumor identification, often matching or exceeding human performance while improving workflow efficiency.
Robot-assisted surgery represents a major advancement, enabling highly precise implant positioning, improved surgical planning, and reduced variability in procedures such as total hip and knee arthroplasty. Despite improved technical accuracy, current evidence shows only modest improvements in short-term clinical outcomes. Additionally, virtual reality technologies are increasingly used for surgical training, planning, and rehabilitation, contributing to improved procedural understanding and patient recovery.
AI also plays a crucial role in postoperative monitoring and rehabilitation through remote data collection, predictive analytics, and personalized therapy adjustments, ultimately reducing complications and readmissions.
Although physician acceptance of AI is growing, challenges remain, including limited knowledge, concerns about reliability, data security, and high implementation costs. Overall, AI is transforming orthopedics by augmenting clinical expertise, enhancing precision, and enabling data-driven, patient-specific care, with continued development and validation necessary for broader clinical integration.

Keywords

artificial intelligence; orthopedics; musculoskeletal imaging; robot-assisted surgery

Hrčak ID:

348440

URI

https://hrcak.srce.hr/348440

Publication date:

25.6.2026.

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