Abstract

This study investigates the emerging role of artificial intelligence (AI) in the diagnosis of varicose veins, a disorder characterised by swollen, convoluted veins that primarily affect the lower limbs and are accompanied by symptoms such as discomfort and edoema. Despite the widespread usage of traditional imaging techniques such as ultrasonography, the risk of human error and the inherent constraints in processing complex visual data demand more robust solutions. We evaluate cutting-edge AI models, particularly those that use deep learning, for their capacity to autonomously analyse imaging data, highlight problematic abnormalities, and aid in clinical decision-making. The study recognises significant advances in algorithmic approaches, evaluates their diagnostic accuracy in comparison to older methods, and analyses the scalability of these solutions for routine clinical application. Furthermore, we discuss the technological and ethical hurdles of integrating AI into medical practice, such as data security, algorithm openness, and regulatory considerations. Our review intends to highlight AI's potential to transform the diagnostic environment for varicose veins, as well as provide insights into practical implementation and future research directions.