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SkinGuard: An EfficientNet Model for Skin Cancer and M-pox Detection

Authors

  • Joel Judish

    Amal Jyothi College of Engineering
    Author
  • Samrudh Salas

    Amal Jyothi College of Engineering,
    Author
  • Farhaan Zuhair

    Amal Jyothi College of Engineering,
    Author
  • Muhammed Zakkariya M

    Amal Jyothi College of Engineering
    Author
  • Juby Mathew

    Amal Jyothi College of Engineering
    Author

Abstract

Skin cancer and monkeypox(mpox) are life threaten- ing conditions that requires early detection and proper treatment to reduce mortality rates. Skin cancer consisting of benign and malignant types are mostly causing widespread due to harmful UV radiation and other genetical disorders. Mpox caused by the monkeypox virus is also causing harmful outbreak among the people making it vunerable to the people around. The traditional methods often fail in detecting it accurately due to lack of medical expertise and are mostly time consuming and expensive. To overcome these challenges,SkinGuard is introduced. SkinGuard is an AI-powered diagnostic system designed to make this process more efficient, accurate, and accessible. It employs the EfficientNet deep learning models to evaluate supplied skin images and identify the abnormalities with high precision. The deep learning model ensures robust feature extraction,classification and differentiation among benign or malignant classes of skin cancer and healthy or mpox classes in monkeypox. The model is trained on a diverse dataset and undergoes various preprocessing techniques like flipping,rotation,resizing,normalization and data augmenta- tion further enhancing its recognition capabilities. Through the leverage of blockchain technology, SkinGuard creates a tamper proof,decentralized medical record sysyem that is impenetrable and offers security,transparency and prevents unauthorized access or data breaches. Additionally its automatic report creation ca- pability allows customers to get clear and thorough information about their diagnostic results,confidence scores and provides pre- liminary recommendations helping both medical professionals and individuals in aiding early assessment. SkinGuard’s dynamic user interface ensures a smooth experience, providing comprehensive dermatological analysis to both medical professionals and the general public. By combining this AI-driven approach with the medical management,SkinGuard provides an additional step in healthcare field providing timely and efficient diagnosis for early detection and treatment.

Keywords:

UV radiation
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Published

20-06-2025

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Articles

How to Cite

[1]
J. Judish, S. Salas, F. Zuhair, M. Zakkariya M, and J. M. Mathew, “SkinGuard: An EfficientNet Model for Skin Cancer and M-pox Detection”, IJERA, vol. 5, no. 1, Jun. 2025, Accessed: Apr. 21, 2026. [Online]. Available: https://ijera.in/index.php/IJERA/article/view/290