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Abstract
This article explores modern methods of digital processing of trichological images for hair condition diagnosis. Special attention is paid to modules that employ computer vision techniques and machine learning algorithms to enhance diagnostic accuracy. Proposed automated image analysis solutions effectively detect hair structure anomalies and simplify the diagnostic process. The article discusses the advantages and limitations of existing approaches and prospects for their further development to improve medical procedures. Applications of these technologies in clinical practice are also examined.
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