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This systematic review examines the applications of artificial intelligence (AI) and robotics in orthopaedic surgery and medical training. The review focuses on robotic navigation, motion control systems, and AI-powered simulation platforms, highlighting their impact on surgical accuracy in procedures like knee arthroplasty and fracture repair, as well as their role in accelerating surgical training. The review identifies challenges including high costs, limited long-term data, and unequal access to technology.
AI and robotic technologies can improve surgical accuracy and training in orthopaedics, but adoption is limited by cost, access, and a lack of long-term data.
Artificial intelligence (AI) and robotics are changing the way orthopedic surgery is performed and taught. This review, conducted using a systematic review approach, looks at how these technologies are being used today, what benefits they bring, what challenges remain, and how they may shape the future. The study focuses on two main areas: surgical improvements and medical training. In surgery, tools such as robotic navigation, motion control systems, and smart prediction models help doctors work with greater accuracy. In education, simulation platforms and AI support systems are giving trainees more confidence and helping them learn faster. The review is based on recent research, including large studies and clinical reports. Results show that robotic-assisted procedures, especially knee operations and fracture repairs, can improve accuracy, reduce complications, and make surgical tasks smoother. Training platforms powered by data also help reduce skills gaps. However, there are still concerns. These include the high cost of adopting technology, limited long-term patient data, and difficulties applying AI models to different healthcare settings. Unequal access to advanced tools and a lack of standard training systems are also slow progress. The review suggests more collaboration, better training standards, and stronger ethical guidelines. While AI and robotics show great promise, future success will depend on real-world testing, fair access, and strong teamwork between humans and machines.
