This study examined the cardiovascular safety of oral minoxidil, used off-label for androgenetic alopecia, particularly as its usage expands in real-world settings, although specific results were not detailed in the abstract.
July 2023 in “Dermatology practical & conceptual” This study developed a support vector machine model using trichoscopic patterns to accurately classify androgenic alopecia severity, with an accuracy of 94.3% in training and 90.0% in test datasets.
5 citations
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January 2025 in “BMC Medical Informatics and Decision Making” This review examines the use of computer vision techniques, specifically deep learning architectures and image processing algorithms, for detecting and assessing skin conditions like vitiligo and dermatitis, and highlights the need for disease-specific datasets to improve automated diagnostic tools in dermatology.
April 2026 in “Scientific Reports” This study presents a new automated computer vision system to objectively measure periocular hair density changes in breast cancer patients undergoing chemotherapy, demonstrating high precision in tracking individual changes and potential as a reliable tool for future clinical trials.
1 citations
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March 2016 in “Current Dermatology Reports” This article reviews the evolution of dermatology surgery training, emphasizing the need for standardized and objective assessment tools for residents, and reports no new clinical results.