Role of Artificial Intelligence in COVID-19 Detection

doi:10.3390/s21238045

. 2021 Dec 1;21(23):8045.

doi: 10.3390/s21238045.

Role of Artificial Intelligence in COVID-19 Detection

Anjan Gudigar¹, U Raghavendra¹, Sneha Nayak¹, Chui Ping Ooi², Wai Yee Chan³, Mokshagna Rohit Gangavarapu¹, Chinmay Dharmik¹, Jyothi Samanth⁴, Nahrizul Adib Kadri⁵, Khairunnisa Hasikin⁵, Prabal Datta Barua^{6

7

8}, Subrata Chakraborty^{8

9}, Edward J Ciaccio¹⁰, U Rajendra Acharya^{11

12

13}

Affiliations

¹ Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India.
² School of Science and Technology, Singapore University of Social Sciences, Singapore 599494, Singapore.
³ Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia.
⁴ Department of Cardiovascular Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal 576104, India.
⁵ Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.
⁶ Cogninet Brain Team, Cogninet Australia, Sydney, NSW 2010, Australia.
⁷ School of Business (Information Systems), Faculty of Business, Education, Law & Arts, University of Southern Queensland, Toowoomba, QLD 4350, Australia.
⁸ Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia.
⁹ Faculty of Science, Agriculture, Business and Law, University of New England, Armidale, NSW 2351, Australia.
¹⁰ Department of Medicine, Columbia University Medical Center, New York, NY 10032, USA.
¹¹ School of Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore.
¹² Department of Biomedical Informatics and Medical Engineering, Asia University, Taichung 41354, Taiwan.
¹³ International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto 860-8555, Japan.

PMID: 34884045
PMCID: PMC8659534
DOI: 10.3390/s21238045

Role of Artificial Intelligence in COVID-19 Detection

Anjan Gudigar et al. Sensors (Basel). 2021.

. 2021 Dec 1;21(23):8045.

doi: 10.3390/s21238045.

Authors

Affiliations

¹ Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India.
² School of Science and Technology, Singapore University of Social Sciences, Singapore 599494, Singapore.
³ Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia.
⁴ Department of Cardiovascular Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal 576104, India.
⁵ Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.
⁶ Cogninet Brain Team, Cogninet Australia, Sydney, NSW 2010, Australia.
⁷ School of Business (Information Systems), Faculty of Business, Education, Law & Arts, University of Southern Queensland, Toowoomba, QLD 4350, Australia.
⁸ Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia.
⁹ Faculty of Science, Agriculture, Business and Law, University of New England, Armidale, NSW 2351, Australia.
¹⁰ Department of Medicine, Columbia University Medical Center, New York, NY 10032, USA.
¹¹ School of Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore.
¹² Department of Biomedical Informatics and Medical Engineering, Asia University, Taichung 41354, Taiwan.
¹³ International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto 860-8555, Japan.

PMID: 34884045
PMCID: PMC8659534
DOI: 10.3390/s21238045

Abstract

The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and affected the livelihood of many more people. Early and rapid detection of COVID-19 is a challenging task for the medical community, but it is also crucial in stopping the spread of the SARS-CoV-2 virus. Prior substantiation of artificial intelligence (AI) in various fields of science has encouraged researchers to further address this problem. Various medical imaging modalities including X-ray, computed tomography (CT) and ultrasound (US) using AI techniques have greatly helped to curb the COVID-19 outbreak by assisting with early diagnosis. We carried out a systematic review on state-of-the-art AI techniques applied with X-ray, CT, and US images to detect COVID-19. In this paper, we discuss approaches used by various authors and the significance of these research efforts, the potential challenges, and future trends related to the implementation of an AI system for disease detection during the COVID-19 pandemic.

Keywords: artificial intelligence; computer-aided diagnostic tool; deep neural networks; hand-crafted feature learning; supervised learning.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

**Figure 1**
Pictorial representation of normal and COVID-19 affected lungs.

**Figure 2**
Overview of the selection process for relevant articles.

**Figure 3**
The complete framework to detect COVID-19 using various approaches.

**Figure 4**
Sample images using various medical image modalities.

**Figure 5**
Percentage of various classes in the assessment of COVID-19 by imaging modalities (X-ray, CT, and X-ray and CT).

**Figure 6**
Comparison of Cvd.Acc, Cvd.Sen, Cvd.Spe, F1-Score, and AUC of AI techniques to detect COVID-19 using box plots.

**Figure 7**
Various methodologies adopted by state-of-the-art techniques using different modalities.

**Figure 8**
IoT-based smart healthcare system to detect COVID-19.

See this image and copyright information in PMC

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References

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[1] Zhu N., Zhang D., Wang W., Li X., Yang B., Song J., Zhao X., Huang B., Shi W., Lu R., et al. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J Med. 2020;382:727–733. doi: 10.1056/NEJMoa2001017. - DOI - PMC - PubMed

[2] Zhu N., Zhang D., Wang W., Li X., Yang B., Song J., Zhao X., Huang B., Shi W., Lu R., et al. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J Med. 2020;382:727–733. doi: 10.1056/NEJMoa2001017. - DOI - PMC - PubMed

[3] Li Q., Guan X., Wu P., Wang X., Zhou L., Tong Y., Ren R., Leung K.S.M., Lau E.H.Y., Wong J.Y., et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. N. Engl. J. Med. 2020;382:1199–1207. doi: 10.1056/NEJMoa2001316. - DOI - PMC - PubMed

[4] Li Q., Guan X., Wu P., Wang X., Zhou L., Tong Y., Ren R., Leung K.S.M., Lau E.H.Y., Wong J.Y., et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. N. Engl. J. Med. 2020;382:1199–1207. doi: 10.1056/NEJMoa2001316. - DOI - PMC - PubMed

[5] Zheng M., Gao Y., Wang G., Song G., Liu S., Sun D., Xu Y., Tian Z. Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Cell. Mol. Immunol. 2020;17:533–535. doi: 10.1038/s41423-020-0402-2. - DOI - PMC - PubMed

[6] Zheng M., Gao Y., Wang G., Song G., Liu S., Sun D., Xu Y., Tian Z. Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Cell. Mol. Immunol. 2020;17:533–535. doi: 10.1038/s41423-020-0402-2. - DOI - PMC - PubMed

[7] Zhang J., Litvinova M., Wang W., Wang Y., Deng X., Chen X., Li M., Zheng W., Yi L., Chen X., et al. Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: A descriptive and modelling study. Lancet Infect. Dis. 2020;20:793–802. doi: 10.1016/S1473-3099(20)30230-9. - DOI - PMC - PubMed

[8] Zhang J., Litvinova M., Wang W., Wang Y., Deng X., Chen X., Li M., Zheng W., Yi L., Chen X., et al. Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: A descriptive and modelling study. Lancet Infect. Dis. 2020;20:793–802. doi: 10.1016/S1473-3099(20)30230-9. - DOI - PMC - PubMed

[9] Cascella M., Rajnik M., Aleem A., Dulebohn S.C., Di Napoli R. Features, Evaluation and Treatment Coronavirus (COVID-19) Stat Pearls Publishing; Treasure Island, FL, USA: 2020. - PubMed

[10] Cascella M., Rajnik M., Aleem A., Dulebohn S.C., Di Napoli R. Features, Evaluation and Treatment Coronavirus (COVID-19) Stat Pearls Publishing; Treasure Island, FL, USA: 2020. - PubMed

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Role of Artificial Intelligence in COVID-19 Detection

Affiliations

Role of Artificial Intelligence in COVID-19 Detection

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Abstract

Conflict of interest statement

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