Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{206778,
author = {Spandana C A and Karan Kumar and Krithi M and Pallavi K and Harishma K V},
title = {Medical Image Analysis System for Burn Detection and Skin Condition Classification Using Deep Learning},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {13},
number = {no},
pages = {435-438},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=206778},
abstract = {Artificial Intelligence has become an important tool in modern healthcare, especially in analyzing medical images for early diagnosis. Detecting burn severity and skin conditions at an early stage is crucial to prevent complications and ensure proper treatment. This paper presents a Medical Image Analysis System that uses deep learning techniques to analyze images of burn injuries and skin lesions. The system classifies burn severity into different levels and predicts skin conditions along with a confidence score. It also provides first-aid guidance and diet recommendations to support user recovery. The system is implemented using Python, with deep learning models such as Convolutional Neural Networks, U-Net, and DenseNet, along with an interactive user interface. The proposed solution aims to provide accessible and efficient healthcare assistance.},
keywords = {.},
month = {July},
}
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