January 2022 in “Journal of Pharmaceutical Negative Results” The VGG-SVM method accurately identifies and classifies stages of Alopecia Areata and other hair loss conditions.
May 2023 in “Indian journal of science and technology” The new deep learning system can accurately recognize hair loss conditions with a 95.11% success rate.
May 2024 in “SPIRE - Sciences Po Institutional REpository” Understanding and treating alopecia areata improves patient care.
5 citations
,
October 2023 in “International Journal on Recent and Innovation Trends in Computing and Communication” The method accurately detects and classifies scalp diseases, including alopecia areata, with 89.3% accuracy.
July 2023 in “Dermatology practical & conceptual” The machine learning model effectively assesses the severity of hair loss and could help dermatologists with treatment decisions.