Implementation of Artificial Intelligence and Big Data to Overcome Covid-19 Pandemic


Artificial Intelligence
Big Data


At this time, where the COVID-19 pandemic caused by a new type of corona virus is occurring, the demands in the health sector are becoming heavy. Seeing the increasing number of confirmed cases of COVID-19 patients and the number of existing cases of death, a solution is needed to deal with this crisis. Artificial Intelligence and Big Data are technologies that can be adapted to deal with the COVID-19 pandemic. This review will discuss how technology based on Artificial Intelligence and Big Data can be implemented to help medical personnel carry out initial diagnoses and various kinds of research to assist drug and vaccine discovery.



H. S. Maghded, K. Z. Ghafoor, A. S. Sadiq, K. Curran, D. B. Rawat, and K. Rabie, “A Novel AI-enabled Framework to Diagnose Coronavirus COVID-19 using Smartphone Embedded Sensors: Design Study,” Proc. - 2020 IEEE 21st Int. Conf. Inf. Reuse Integr. Data Sci. IRI 2020, pp. 180–187, 2020, doi: 10.1109/IRI49571.2020.00033.

Q. V. Pham, D. C. Nguyen, T. Huynh-The, W. J. Hwang, and P. N. Pathirana, “Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts,” IEEE Access, vol. 8, no. April, pp. 130820–130839, 2020, doi: 10.1109/ACCESS.2020.3009328.

D. Barragán and J. Manero, “How Big Data and Artificial Intelligence Can Help Against COVID-19,” IE Bus. Sch., pp. 4–11, 2020, [Online]. Available:

A. Martin et al., “An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot,” Sci. Rep., vol. 10, no. 1, pp. 1–7, 2020, doi: 10.1038/s41598-020-75912-x.

X. Li, C. Li, and D. Zhu, “COVID-MobileXpert: On-Device COVID-19 Patient Triage and Follow-up using Chest X-rays,” Proc. - 2020 IEEE Int. Conf. Bioinforma. Biomed. BIBM 2020, pp. 1063–1067, 2020, doi: 10.1109/BIBM49941.2020.9313217.

X. Mei et al., “Artificial intelligence–enabled rapid diagnosis of patients with COVID-19,” Nat. Med., vol. 26, no. 8, pp. 1224–1228, 2020, doi: 10.1038/s41591-020-0931-3.

J. Bullock, A. Luccioni, K. H. Pham, C. S. N. Lam, and M. Luengo-Oroz, “Mapping the landscape of artificial intelligence applications against COVID-19,” J. Artif. Intell. Res., vol. 69, pp. 807–845, 2020, doi: 10.1613/JAIR.1.12162.

Z. Xiong et al., “Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT,” Radiology, vol. 296, no. 3, pp. E156–E165, 2020, doi: 10.1148/radiol.2020201491.

C. Jin et al., “Development and evaluation of an artificial intelligence system for COVID-19 diagnosis,” Nat. Commun., vol. 11, no. 1, 2020, doi: 10.1038/s41467-020-18685-1.

A. Abdulaal, A. Patel, E. Charani, S. Denny, N. Mughal, and L. Moore, “Prognostic modeling of COVID-19 using artificial intelligence in the United Kingdom: Model development and validation,” J. Med. Internet Res., vol. 22, no. 8, pp. 1–10, 2020, doi: 10.2196/20259.

R. Vaishya, M. Javaid, I. H. Khan, and A. Haleem, “Artificial Intelligence (AI) applications for COVID-19 pandemic,” Diabetes Metab. Syndr. Clin. Res. Rev., vol. 14, no. 4, pp. 337–339, 2020, doi: 10.1016/j.dsx.2020.04.012.