Deep Learning-Based Prediction of Lung Disease: A Comprehensive Analysis and Proposed Methodology

Naveen Kumar Navuri; Mundrika Tejasri; Pakirla Veera Pavani; Pasupuleti Gokul Venkat Uday

doi:10.55524/ijirem.2026.13.2.9

Abstract

Early diagnosis of lung diseases is very essential in ensuring fewer deaths and better treatment to the patient. One of the most widely applied techniques of diagnosing lung conditions is the chest X-ray, which can be occasionally slow to interpret manually and differs according to the experience of the medical practitioner. To overcome these difficulties, this study will offer an Intelligent Lung Disease Prediction System where a hybrid deep learning method will be applied to the analysis of chest X-ray images using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. The model is formed to differentiate between the X-ray images by categorizing them into three different classes, namely, Normal, Viral Pneumonia, and Lung Opacity. To obtain the spatial features effectively out of the images, they utilize a pre-trained ResNet50 model but, to extract more relations between the extracted features in order to enhance the classification performance, they make use of the LSTM layer. To make the system more intuitive and transparent, the model is combined with the Grad-CAM visualization that brings out the particular parts of the X-ray image that affect the predictions of the model. This assists the users to know where the model is focusing on towards the detection of possible abnormalities. The trained model is deployed as a web application written in Flask, where users upload images of their chest X-rays and receive real-time predictions with visual explanations. The site also incorporates facilitating features like simplistic health tips and the co-opetition on whether to visit the doctor, which make it more practical. On the whole, this system shows that deep learning methods can be utilized to aid in early detection of lung diseases and increase the availability of initial medical examinations.

Keywords

Lung Disease Detection, Chest X-ray Classification, Deep Learning, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM)

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Cites this article as

N. K. Navuri, M. Tejasri, . P. V. Pavani, P. G. V. Uday, "Deep Learning-Based Prediction of Lung Disease: A Comprehensive Analysis and Proposed Methodology", International Journal of Innovative Research in Engineering and Management (IJIREM), Vol-13, Issue-2, Page No-62-67, 2026. Available from: https://doi.org/10.55524/ijirem.2026.13.2.9

Corresponding Author

Naveen Kumar Navuri

Department of Computer Science and Engineering, Malla Reddy University, Hyderabad, India

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