The use of artificial intelligence in treating knee osteoarthritis: a review

Abstract

Osteoarthritis (OA) is the most common progressive musculoskeletal condition in adults affecting the joints. Usually, it mainly targets weight-bearing joints such as the hips and knees. Knee OA is characterized by structural modifications to primarily articular cartilage and the subchondral bone. The prevalence of knee OA has increased significantly over the past few decades and continues to increase, partly due to the increased prevalence of obesity, age, gender, and other risk factors, but also independently, from other causes. Knee OA poses significant challenges in diagnosis, treatment, and management. Artificial intelligence (AI) has the potential to make substantial progress toward the goal of making healthcare more personalized, predictive, preventative, and interactive. It is believable that AI will continue its present path and ultimately become a mature and effective tool for the healthcare sector.  AI has emerged as a powerful tool with the potential to revolutionize knee OA diagnosis, treatment, and management. This review explores the current application of AI in knee OA, its potential benefits, and ongoing challenges. It suggests that AI has the potential to improve diagnostic accuracy, optimize treatment strategies, and enhance patient outcomes. However further research is needed to address limitations and explore the full potential of AI in revolutionizing knee OA management.