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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM49905
Volume:
9 |
6 |
Jun 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Millions of people worldwide suffer from skin conditions, which, if not identified and treated promptly, can result in serious health issues. The lack of dermatologists and the difficulty of visual diagnosis make timely detection difficult even with advancements in medical technology. In this project, we use Convolutional Neural Networks (CNN) and sophisticated architectures such as ResNet-50 to propose a deep learning-based system for automatic skin disease detection and treatment recommendation. The system categorizes illnesses, suggests treatments, and determines the severity to help users decide whether to see a doctor. In remote or underserved areas, this automated method can help medical professionals and be implemented as a scalable solution for early skin disease diagnosis.
KEYWORDS
Publication Date
11/5/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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