research Automated Trichoscopic Analysis for Hair Disorder Classification Using Semantic Segmentation
This study developed an automated image analysis framework for diagnosing hair disorders using trichoscopic images, reporting a Random Forest classifier as having an 86.67% accuracy in distinguishing between different scalp pathologies based on quantitative image features.



