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A Review of Recent Deep Learning Models in COVID-19 Diagnosis

Author

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  • Ela Bhattacharya

    (Indian Institute of Technology Bhubaneswar, India)

  • D. Bhattacharya

    (R. G. Kar Medical College and Hospital, India)

Abstract

COVID-19 has emerged as the latest worrisome pandemic, which is reported to have its outbreak in Wuhan, China. The infection spreads by means of human contact, as a result, it has caused massive infections across 200 countries around the world. Artificial intelligence has likewise contributed to managing the COVID-19 pandemic in various aspects within a short span of time. Deep Neural Networks that are explored in this paper have contributed to the detection of COVID-19 from imaging sources. The datasets, pre-processing, segmentation, feature extraction, classification and test results which can be useful for discovering future directions in the domain of automatic diagnosis of the disease, utilizing artificial intelligence-based frameworks, have been investigated in this paper.

Suggested Citation

  • Ela Bhattacharya & D. Bhattacharya, 2021. "A Review of Recent Deep Learning Models in COVID-19 Diagnosis," European Journal of Engineering and Technology Research, European Open Science, vol. 6(5), pages 10-15, July.
    • Handle: RePEc:epw:ejeng0:v:6:y:2021:i:5:id:62485
    DOI: 10.24018/ejeng.2021.6.5.2485
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