February 2024 in “Frontiers in physics” This study developed a model for detecting sparse hair clusters using enhanced object detection neural networks and medical images, which accurately identifies and counts sparse hair clusters with greater accuracy and efficiency than existing methods.
This study developed a digital tool for quantitatively assessing hair in androgenetic alopecia, achieving an average accuracy of 79.45% for counting hairs and 68.19% for measuring hair size compared to human evaluation.
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January 2023 in “IEEE access” This review examines advancements in deep learning methods for detecting dermatological conditions from dermoscopic images, summarizing available datasets and suggesting future research directions, but reports no new results.
Dermatologists help detect gender-based violence by identifying skin signs of abuse.
August 2016 in “PolyPublie (École Polytechnique de Montréal)” This study observed early cardiac effects in young minipigs following high-dose doxorubicin chemotherapy, with a decrease in heart function and changes in cardiac MRI measurements compared to controls.