Pneumonia Detection Using Deep Learning

Sreevarshini Aireddy, Maruthi Sanjana, Palle Uday Kiran Goud, Mattipatti Sameer, Myla Kalyana Ramakrishna, D. Archana

2025

Abstract

Pneumonia is a serious lung infection that mainly affects children and the elderly people which requires rapid and accurate diagnosis. There are simple and effective methods for pneumonia detection, including the deep learning techniques, such as the convolutional neural network (CNN). As of now, such techniques have proved potential for medical image classification. In this paper, we present a pneumonia detection model built using the VGG16 pre-trained model of convolutional neural network architecture and trained on a labeled dataset of the chest X-ray images. The proposed system implementation is evaluated for its performance and also compared with the traditional methods, which show the significantly improved accuracy. This paper mostly exhibits the potential of transfer learning and using data augmentation to improve model generalization. This model was trained and tested on a chest X-ray image of a labeled dataset, obtaining the accuracy of around 93%. This system is deployed with a local web-based interface, which allowed the users to upload chest X-ray images for the real-time classification. The results show that deep learning can significantly improve the pneumonia detection, providing a more efficient, accurate, and automated alternative to existing diagnostic techniques.

Paper Citation

in Harvard Style

Aireddy S., Sanjana M., Goud P., Sameer M., Ramakrishna M. and Archana D. (2025). Pneumonia Detection Using Deep Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 75-80. DOI: 10.5220/0013908400004919

in Bibtex Style

@conference{icrdicct`2525,
author={Sreevarshini Aireddy and Maruthi Sanjana and Palle Goud and Mattipatti Sameer and Myla Ramakrishna and D. Archana},
title={Pneumonia Detection Using Deep Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={75-80},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013908400004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Pneumonia Detection Using Deep Learning
SN - 978-989-758-777-1
AU - Aireddy S.
AU - Sanjana M.
AU - Goud P.
AU - Sameer M.
AU - Ramakrishna M.
AU - Archana D.
PY - 2025
SP - 75
EP - 80
DO - 10.5220/0013908400004919
PB - SciTePress