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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 14, ISSUE 1, JANUARY 2025

Pneumonia Detection Using Deep Learning

Snitha Shetty, S Aravind, Kevin Samu, Muhammed Rafad P, Sarang A VC

DOI: 10.17148/IJARCCE.2025.14119

Abstract: Pneumonia is a serious lung infection that afflicts millions worldwide, particularly children and the elderly. To be treated effectively, this requires prompt and accurate diagnosis. This project introduces a system that uses Convolutional Neural Networks (CNNs), a powerful deep learning tool, to make pneumonia detection easier and faster. Users can upload chest X-ray images, which the CNN model will analyze to identify signs of pneumonia with high accuracy and speed. By bringing the efficiency of advanced image analysis together with a user-friendly interface, this approach should bring diagnostic capabilities closer while improving issues such as data quality, privacy, and model reliability.

Keywords: Pneumonia, Convolutional neural network, Data augmentation, Deep learning, Accuracy.

How to Cite:

[1] Snitha Shetty, S Aravind, Kevin Samu, Muhammed Rafad P, Sarang A VC, “Pneumonia Detection Using Deep Learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14119