Artificial intelligence algorithms in orthopaedics: A narrative review of methods and clinical applications.

ABSTRACT: This narrative review evaluates the role of artificial intelligence (AI) algorithms in orthopaedic surgery and distinguishes itself by explaining how the main algorithmic approaches function and illustrating each with orthopaedic examples. Machine learning methods, including regression, classification and reinforcement learning, have been applied to fracture detection, prediction of revision risk and modelling of outcomes after arthroplasty and sports injury. Deep learning and convolutional neural networks have improved fracture classification, implant surveillance and segmentation of cartilage and meniscal tissue on magnetic resonance imaging. Neural networks such as FracNet and YOLO-based systems demonstrate growing capability in trauma imaging. Natural language processing has automated

SUBMITTER: Rosen J 

PROVIDER: S-EPMC12616508 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature