Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2024 Apr 10:12:1386110.
doi: 10.3389/fpubh.2024.1386110. eCollection 2024.

Artificial intelligence in the healthcare sector: comparison of deep learning networks using chest X-ray images

M Akif Yenikaya  1 , Gökhan Kerse  1 , Onur Oktaysoy  1
Affiliations
Comparative Study

Artificial intelligence in the healthcare sector: comparison of deep learning networks using chest X-ray images

M Akif Yenikaya et al. Front Public Health. .

Abstract

Purpose: Artificial intelligence has led to significant developments in the healthcare sector, as in other sectors and fields. In light of its significance, the present study delves into exploring deep learning, a branch of artificial intelligence.

Methods: In the study, deep learning networks ResNet101, AlexNet, GoogLeNet, and Xception were considered, and it was aimed to determine the success of these networks in disease diagnosis. For this purpose, a dataset of 1,680 chest X-ray images was utilized, consisting of cases of COVID-19, viral pneumonia, and individuals without these diseases. These images were obtained by employing a rotation method to generate replicated data, wherein a split of 70 and 30% was adopted for training and validation, respectively.

Results: The analysis findings revealed that the deep learning networks were successful in classifying COVID-19, Viral Pneumonia, and Normal (disease-free) images. Moreover, an examination of the success levels revealed that the ResNet101 deep learning network was more successful than the others with a 96.32% success rate.

Conclusion: In the study, it was seen that deep learning can be used in disease diagnosis and can help experts in the relevant field, ultimately contributing to healthcare organizations and the practices of country managers.

Keywords: COVID-19; artificial intelligence; deep learning; healthcare organizations; healthcare sector; viral pneumonia.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Reproduction of X-ray data.
Figure 2
Figure 2
Deep learning flow chart.
Figure 3
Figure 3
ResNet101 cycle-accuracy and cycle-loss graphs.
Figure 4
Figure 4
ResNet101 confusion matrix.
Figure 5
Figure 5
AlexNet cycle-accuracy and cycle-loss graphs.
Figure 6
Figure 6
AlexNet confusion matrix.
Figure 7
Figure 7
GoogLeNet cycle-accuracy and cycle-loss graphs.
Figure 8
Figure 8
GoogLeNet confusion matrix.
Figure 9
Figure 9
Xception cycle-accuracy and cycle-loss graphs.
Figure 10
Figure 10
Xception confusion matrix.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Bloom D E, Cadarette D, Sevilla J. Epidemics and economics: New and resurgent infectious diseases can have far-reaching economic repercussions. Financ Dev. (2018). 55:46–49.
    1. Wüllner S, Hermenau K, Krutkova M, Petras IK, Hecker T, Siniatchkin M. Mobile applications in adolescent psychotherapy during the COVID-19 pandemic: a systematic review. Front Public Health. (2024) 12:1345808. doi: 10.3389/fpubh.2024.1345808 - DOI - PMC - PubMed
    1. Bloom E, DeWıt V, Carangal-San Jose MJ. Potential economic impact of an avian flu pandemic on Asia. Philippines: Asian Development Bank; (2005).
    1. Ekpenyong A, Pacheco MS. COVID-19: reflecting on the role of the WHO in knowledge exchange between the global north and south. Glob Soc Policy. (2020) 20:388–92. doi: 10.1177/1468018120966657 - DOI
    1. World Bank . Spread of avian flu could affect next year’s economic outlook. In World Bank . (eds.) East Asia update – countering global shocks. (2005) World Bank Press, USA

Publication types

Grants and funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
-