April 2023 in “Journal of Investigative Dermatology” The improved EczemaNet more reliably and clearly identifies and assesses the severity of atopic dermatitis from photos.
November 2024 in “Image Analysis & Stereology” The method improves hair image segmentation accuracy while reducing annotation costs.
February 2023 in “International Journal of Multimedia Computing” The improved algorithm enhances low-dose CT image quality significantly better than other methods.
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December 2022 in “JAMA Dermatology” The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
February 2024 in “Frontiers in physics” The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.