Automated Early Detection Of Androgenetic Alopecia Using Deep Learning On Trichoscopic Images From A Korean Cohort: A Retrospective Model Development And Validation Study
July 2025
in “
Harvard Dataverse
”
TLDR A deep learning model accurately detects early hair loss signs using scalp images.
The study focuses on developing and validating a deep learning model for the early detection of androgenetic alopecia using trichoscopic images from a Korean cohort. This retrospective study highlights the potential of artificial intelligence in diagnosing hair loss conditions by analyzing scalp images. The model's performance was evaluated, demonstrating its effectiveness in identifying early signs of androgenetic alopecia, which could lead to timely interventions and better management of the condition. The use of a Korean cohort provides valuable insights into the applicability of the model across different populations.
