Diagnosis of COVID-19 CT Scans Using Convolutional Neural Networks

Victor Chang*, Siddharth Mcwann, Karl Hall, Qianwen Ariel Xu, Meghana Ashok Ganatra

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Machine learning technology, particularly neural networks, provides useful tools for diagnosing diseases. This study focuses on how convolutional neural networks can be implemented to diagnose COVID-19 through the processing of x-ray images. This study demonstrates how the convolutional neural networks DenseNet201, ResNet152, VGG16, and InceptionV3 can aid healthcare providers in the diagnosis of COVID-19. The models returned accuracies of 98.73%, 97.23%, 91.25% and 98.38% respectively. The results from these experiments are compared to previous studies by evaluating F1-score, accuracy, precision and recall. Additionally, the important problems of hyperparameter tuning and data imbalance are explored and addressed. Areas for future research in this area are also suggested.
Original languageEnglish
Article number625
Number of pages17
JournalSN Computer Science
Volume5
Issue number5
Early online date7 Jun 2024
DOIs
Publication statusPublished - Jun 2024

Bibliographical note

Copyright © The Author(s), 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.

Keywords

  • Artificial intelligence
  • COVID-19
  • Convolutional neural networks
  • Diagnosis
  • Healthcare systems
  • Machine learning

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