Classification of Visually Similar Scalp Diseases Using Deep Learning: A Hybrid CNN-VIT Approach With Cross-Attention Fusion

    June 2026 in “ Zenodo (CERN European Organization for Nuclear Research) ”
    Ayushi Dixit, Dr. Brij Mohan Singh

    Preprint — not peer reviewed. This was posted to a preprint server or data repository. It has not been through a journal's review process, and its findings may change or not hold up.

    Studysummary In this study, researchers developed a hybrid deep learning model called ScalpViT that accurately diagnosed scalp diseases with 94.3% accuracy, surpassing existing methods like ResNet-50 and EfficientNet-B3, and providing visual explainability for clinicians using GradCAM and Attention Rollout techniques.
    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
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