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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM54737
Volume:
9 |
11 |
Nov 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.
Early and accurate detection of lung diseases such as Pneumonia, Tuberculosis, COVID-19, and Lung Cancer is crucial for timely medical intervention. This project presents an intelligent, explainable deep-learning–based web application that analyzes chest X-ray images and provides disease classification along with visual explanations to improve trust and interpretability. A Convolutional Neural Network (ResNet-based model) is trained to classify lung conditions, and the system integrates Explainable AI (XAI) techniques—Grad-CAM and LIME—to highlight the specific regions in the X-ray that influence the prediction. These visual explanations help doctors and users understand why the model makes a particular decision.
KEYWORDS
Publication Date
1/11/2025
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.
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No funding information available for this research.
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