골관절염에서 인공지능의 역할 및 적용

초록

Osteoarthritis (OA) is one of the most prevalent degenerative joint diseases worldwide, with an increasing incidence because of the aging population and increasing obesity rates. The condition significantly reduces the quality of life, particularly in elderly populations, and remains a major cause of disability. Current diagnostic and treatment approaches face substantial challenges, including the lack of reliable biomarkers for early diagnosis and accurate predictions of disease progression. Recent advances in artificial intelligence (AI), particularly machine learning and deep learning, have introduced groundbreaking opportunities in OA research. AI-based imaging analysis techniques have enhanced the diagnostic accuracy and efficiency compared to traditional methods. Furthermore, AI methodologies incorporating multiomics data analysis provide insights into the complex molecular characteristics of OA, enabling the development of personalized treatment strategies tailored to the individual patient profiles. This review explores current AI research trends in OA, evaluates the practical clinical applications of AI technologies, and discusses their performance and limitations. In addition, the key challenges and potential strategies for integrating AI successfully into clinical practice are highlighted. Ultimately, this study underscores the potential of AI to transform prevention, diagnosis, and treatment approaches in OA healthcare.

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