Image

    Classification Framework for Healthy Hair and Alopecia Areata: A Machine Learning Approach

    August 2021 in “ Computational and Mathematical Methods in Medicine ”
    Choudhary Sobhan Shakeel, Saad Jawaid Khan, Beenish Moalla Chaudhry … Umer Hassan
    Studysummary This article proposes a machine learning framework for classifying healthy hair and alopecia areata using image processing and classification techniques, but does not report new clinical findings.
    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 downloads.hindawi.com →
    Discuss this study in the Community →

    Research cited in this study 7

    1. Alopecia Areata: A Review on Diagnosis, Immunological Etiopathogenesis, and Treatment Options Clinical and Experimental Medicine · 2021
    2. Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue Computational and Mathematical Methods in Medicine · 2020
    3. Pre-Trained Classification of Scalp Conditions Using Image Processing Indonesian Journal of Electrical Engineering and Computer Science · 2020
    4. Alopecia Areata: A Multifactorial Autoimmune Condition Journal of autoimmunity · 2018
    5. Quantifying Alopecia Areata via Texture Analysis to Automate the SALT Score Computation Journal of Investigative Dermatology Symposium Proceedings · 2017
    6. New-Generation Therapies for the Treatment of Hair Loss in Men Dermatologic Clinics · 2017
    7. TrichoScan: A Novel Tool for the Analysis of Hair Growth In Vivo Journal of Investigative Dermatology Symposium Proceedings · 2003