12 citations
,
May 2011 in “Dermatologic Clinics” This review discusses the association between scarring alopecia and inflammatory processes in common acquired bullous disorders of the scalp, and reports no new clinical findings.
July 2022 in “International Journal of Applied Pharmaceutics” This research explored the use of machine learning and deep learning methods to accurately identify alopecia areata in humans by analyzing facial images and demonstrated the potential of these techniques for medical, security, and commercial applications.
January 2026 in “Journal of Investigative Dermatology” Female-pattern hair loss may involve an autoimmune-like process, suggesting new treatment options.
5 citations
,
July 2023 in “Journal of Autonomous Intelligence” This study evaluates a framework using neural networks and machine learning techniques to classify and detect Alopecia Areata from hair images, aiming for accurate differentiation between healthy hair and the condition.
3 citations
,
October 1982 in “Postgraduate Medicine” This article discusses objective methods for assessing hair loss and notes that most types of hair loss can regrow without treatment, but effective treatments for pattern or senescent alopecia remain unavailable.