4 citations
,
December 2021 in “Electronics” The new method predicts post-hair transplant images more accurately than other methods.
February 2023 in “International Journal of Multimedia Computing” The improved algorithm enhances low-dose CT image quality significantly better than other methods.
9 citations
,
September 2022 in “Frontiers in Physics” The technique accurately identifies and evaluates hair follicle structures in skin.
January 2021 in “arXiv (Cornell University)” Self-supervised learning improves medical image classification accuracy.
April 2023 in “Journal of Investigative Dermatology” The improved EczemaNet more reliably and clearly identifies and assesses the severity of atopic dermatitis from photos.