8 citations
,
August 2021 in “Computational and Mathematical Methods in Medicine” Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
2 citations
,
January 2024 in “Journal of Emerging Investigators” A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
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.
8 citations
,
November 2022 in “International Journal of Cosmetic Science” Human hair varies widely and should be classified by curl type rather than race.
March 2026 in “Frontiers in Medicine” A hybrid model using traditional methods, trichoscopy, and AI improves hair loss assessment.