Identification and classification of musculoskeletal conditions using artificial intelligence and machine learning

Musculoskeletal conditions are a complicated health care problem because they are extremely common but also characterized by a wide range of complexity in their diagnosis and treatment. This chapter explores how artificial intelligence (AI) and machine learning (ML) could transform the identification and classification of such conditions. The chapter discusses the latest advances in AI-driven diagnostics, noting that these algorithms could enable more accurate medical imaging analysis, supporting early detection and accurate diagnosis of arthritis or fractures. The chapter also discusses the advancement of personalized treatment plans after the deep data analysis that AI affords, emphasizing the realization of better patient outcomes. Areas of note center on infusing AI into precision surgery and rehabilitation so that AI-assisted procedures and AI-powered wearables enhance the best strategies for recovery. Further, the chapter covers the application of predictive analytics in preventive care, in which AI is used to identify risk factors and formulate preemptive strategies. Despite these promising developments, this chapter addresses challenges and ethical questions that should be considered when designing AI to implement it in musculoskeletal medicine, such as issues of data privacy, validation of AI tools, and complexities of musculoskeletal diseases. This chapter gives a full overview of today's AI and ML status and the future potential for musculoskeletal medicine with its impact on diagnostics, treatment, and rehabilitation.