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September 5, 2025Asian Journal of Engineering and Applied Technology

An AI-based System for Pneumonia Detection in Chest X-Rays Using Deep Learning Models

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Authors

SNS. NikithaHSH. P. SudhanvaTNT. A. Nayana

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Overview

This AI-based system enhances pneumonia detection accuracy in chest X-rays, indicating potential clinical application.

Key Points

  • ResNet50 achieved the highest detection accuracy of 95.2%, indicating strong model performance for pneumonia.
  • Enhanced image processing methods, including multi-CLAHE and synthetic data, improved detection capabilities significantly.
  • The study utilized three deep learning models—VGG16, VGG19, and ResNet50—to evaluate diagnostic effectiveness.
  • AI-assisted diagnosis has the potential to improve clinical outcomes for pneumonia detection in resource-limited settings.

Cite This Study

Nikitha et al. (2025) studied this question.

synapsesocial.com/papers/68c23922b210217d6477b05ehttps://doi.org/10.70112/ajeat-2025.14.1.4278
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1AI-Powered Pneumonia Detection Using Deep Learning on Chest X-Ray Images2025
  2. 2Automated Pneumonia Detection With Deep Learning Methods2025
  3. 3Deep Learning-Based Pneumonia Detection from Chest X-ray Images: A CNN Approach with Performance Analysis and Clinical Implications2025
  4. 4Deep Learning Models for Multi-class Pneumonia Detection in Chest X-rays: A Comparative Study of VGG16, MobileNet, and ResNet1522025
  5. 5Deep Learning Models for Multi-class Pneumonia Detection in Chest X-rays: A Comparative Study of VGG16, MobileNet, and ResNet1522025