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Towards classification and comprehensive analysis of AI-based COVID-19 diagnostic techniques: : A survey

Published: 01 May 2024 Publication History

Abstract

The unpredictable pandemic came to light at the end of December 2019, known as the novel coronavirus, also termed COVID-19, identified by the World Health Organization (WHO). The virus first originated in Wuhan (China) and rapidly affected most of the world's population. This outbreak's impact is experienced worldwide because it causes high mortality risk, many cases, and economic falls. Around the globe, the total number of cases and deaths reported till November 12, 2022, were >600 million and 6.6 million, respectively. During the period of COVID-19, several diverse diagnostic techniques have been proposed. This work presents a systematic review of COVID-19 diagnostic techniques in response to such acts. Initially, these techniques are classified into different categories based on their working principle and detection modalities, i.e. chest X-ray imaging, cough sound or respiratory patterns, RT-PCR, antigen testing, and antibody testing. After that, a comparative analysis is performed to evaluate these techniques' efficacy which may help to determine an optimum solution for a particular scenario. The findings of the proposed work show that Artificial Intelligence plays a vital role in developing COVID-19 diagnostic techniques which support the healthcare system. The related work can be a footprint for all the researchers, available under a single umbrella. Additionally, all the techniques are long-lasting and can be used for future pandemics.

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Highlights

We proposed a Systematic Literature Review (SLR) related to COVID-19 diagnostic techniques in response to the pandemic.
Initially, these techniques are classified into different categories based on their working principle and detection modalities, i.e. chest X-ray imaging, cough sound or respiratory patterns, RT-PCR, antigen testing, and antibody testing.
After that, a comparative analysis is performed to evaluate these techniques' efficacy which may help to determine an optimum solution for a particular scenario.
The findings of the proposed work show that Artificial Intelligence plays a vital role in developing COVID-19 diagnostic techniques which support the healthcare system.
The existing research work can be a footprint for all the researchers, available under a single umbrella. Additionally, all the techniques are longlasting and can be used for future pandemics.

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cover image Artificial Intelligence in Medicine
Artificial Intelligence in Medicine  Volume 151, Issue C
May 2024
297 pages

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Elsevier Science Publishers Ltd.

United Kingdom

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Published: 01 May 2024

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  1. COVID-19
  2. Coronavirus
  3. Pandemic
  4. Diagnostic techniques
  5. Artificial intelligence
  6. Machine learning
  7. Deep learning

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