USE OF ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS AND TREATMENT OF ORTHOPEDIC DISEASES: LITERATURE REVIEW.

Abstract

INTRODUCTION: Artificial intelligence techniques such as machine learning have made it possible to create neural networks for the recognition of MRI and X-ray images, which has improved the diagnosis and treatment of orthopedic diseases. The purpose of our review was to synthesize and analyze publications on the use of artificial intelligence in the diagnosis and treatment of diseases of the musculoskeletal system. MATERIALS AND METHODS: Utilizing a systematic narrative review method, we evaluated 348 publications from 2019 to 2024, with 201 of these being openly accessible. These publications were sourced from the Scopus and PubMed databases, focusing on key terms such as "Machine Learning", "Orthopedic Diagnostics", "Virtual Reality", and "Diseases of the Musculoskeletal System". We selected 89 publications for detailed analysis to identify the primary AI methods employed in orthopedics and to assess their diagnostic and therapeutic efficacy. During the literature analysis, the main areas were determined: the main methods of artificial intelligence used in orthopedics and the results of their application for diagnosis and treatment. RESULTS: The analysis of publications showed the effectiveness of the use of AI in the analysis of MRI, CT and X-ray images. Techniques used by AI, such as machine learning, deep learning, virtual reality, and their effectiveness in performing diagnostic and treatment procedures were considered. CONCLUSIONS: The use of artificial intelligence in the diagnosis and treatment of orthopedic diseases demonstrated an increase in diagnostic accuracy, which contributed improvement of treatment results.

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