An Analysis of Alopecia Areata Classification Framework for Human Hair Loss Based on VGG-SVM Approach
January 2022
in “
Journal of Pharmaceutical Negative Results
”
Studysummary This study found that a VGG-SVM model using machine learning techniques achieved 98.31% accuracy in distinguishing alopecia areata from healthy hair based on image datasets.
Automatically generated from the study's abstract, not written by a person, and not a review of the full paper. Not medical advice or a treatment recommendation. Read the original study, and consult a qualified healthcare professional before changing treatment. Full disclaimer
Read the full study on pnrjournal.com →