The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy
  • Promote your Publication

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Automated Pneumonia Diagnosis using a 2D Deep Convolutional Neural Network with Chest X-Ray Images

Author 1: Kamila Kassylkassova
Author 2: Batyrkhan Omarov
Author 3: Gulnur Kazbekova
Author 4: Zhadra Kozhamkulova
Author 5: Mukhit Maikotov
Author 6: Zhanar Bidakhmet

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2023.0140281

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 2, 2023.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Tiny air sacs in one or both lungs become inflamed as a result of the lung infection known as pneumonia. In order to provide the best possible treatment plan, pneumonia must be accurately and quickly diagnosed at initial stages. Nowadays, a chest X-ray is regarded as the most effective imaging technique for detecting pneumonia. However, performing chest X-ray analysis may be quite difficult and laborious. For this purpose, in this study we propose deep convolutional neural network (CNN) with 24 hidden layers to identify pneumonia using chest X-ray images. In order to get high accuracy of the proposed deep CNN we applied an image processing method as well as rescaling and data augmentation methods as shear_range, rotation, zooming, CLAHE, and vertical_flip. The proposed approach has been evaluated using different evaluation criteria and has demonstrat-ed 97.2%, 97.1%, 97.43%, 96%, 98.8% performance in terms of accuracy, precision, recall, F-score, and AUC-ROC curve. Thus, the applied deep CNN obtain a high level of performance in pneumonia detection. In general, the provided approach is intended to aid radiologists in making an accurate pneumonia diagnosis. Additionally, our suggested models could be helpful in the early detection of other chest-related illnesses such as COVID-19.

Keywords: Pneumonia; deep learning; CNN; chest X-rays; radiology

Kamila Kassylkassova, Batyrkhan Omarov, Gulnur Kazbekova, Zhadra Kozhamkulova, Mukhit Maikotov and Zhanar Bidakhmet, “Automated Pneumonia Diagnosis using a 2D Deep Convolutional Neural Network with Chest X-Ray Images” International Journal of Advanced Computer Science and Applications(IJACSA), 14(2), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140281

@article{Kassylkassova2023,
title = {Automated Pneumonia Diagnosis using a 2D Deep Convolutional Neural Network with Chest X-Ray Images},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140281},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140281},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {2},
author = {Kamila Kassylkassova and Batyrkhan Omarov and Gulnur Kazbekova and Zhadra Kozhamkulova and Mukhit Maikotov and Zhanar Bidakhmet}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2023

2-3 March 2023

  • Virtual

Computing Conference 2023

22-23 June 2023

  • London, United Kingdom

IntelliSys 2023

7-8 September 2023

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2023

2-3 November 2023

  • San Francisco, United States
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org