Next Article in Journal
The History of Anti-Trypanosome Vaccine Development Shows That Highly Immunogenic and Exposed Pathogen-Derived Antigens Are Not Necessarily Good Target Candidates: Enolase and ISG75 as Examples
Next Article in Special Issue
Antibiotic Resistance and Virulence Profiles of Escherichia coli Strains Isolated from Wild Birds in Poland
Previous Article in Journal
Pragmatic Strategy for Fecal Specimen Storage and the Corresponding Test Methods for Clostridioides difficile Diagnosis
Previous Article in Special Issue
Detection and Characterization of Clinical Bordetella trematum Isolates from Chronic Wounds
 
Search for Articles:
Title / Keyword
Author / Affiliation
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
Journals
Pathogens
Volume 10
Issue 8
10.3390/pathogens10081048
pathogens-logo
Submit to this Journal Review for this Journal Edit a Special Issue
► Article Menu

Article Menu

share announcement question_answer thumb_up
...
textsms
...
Review

Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19

by
Gunjan Arora
1,*,†,
Jayadev Joshi
2,†,
Rahul Shubhra Mandal
3,
Nitisha Shrivastava
4,
Richa Virmani
5 and
Tavpritesh Sethi
6
1
Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06520, USA
2
Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA
3
Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
4
Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY 10461, USA
5
Confo Therapeutics, Technologiepark 94, 9052 Ghent, Belgium
6
Indraprastha Institute of Information Technology, New Delhi 110020, India
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this paper.
Academic Editor: Jorge Luis Espinoza
Pathogens 2021, 10(8), 1048; https://doi.org/10.3390/pathogens10081048
Received: 9 June 2021 / Revised: 11 August 2021 / Accepted: 11 August 2021 / Published: 18 August 2021
(This article belongs to the Special Issue Detection and Characterization of Drug-Resistant Organisms)
View Full-Text Download PDF
Browse Figures

Abstract

As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic since the 1918 flu. The main challenges in mitigating COVID-19 are effective vaccination, treatment, and agile containment strategies. In this review, we focus on the potential of Artificial Intelligence (AI) in COVID-19 surveillance, diagnosis, outcome prediction, drug discovery and vaccine development. With the help of big data, AI tries to mimic the cognitive capabilities of a human brain, such as problem-solving and learning abilities. Machine Learning (ML), a subset of AI, holds special promise for solving problems based on experiences gained from the curated data. Advances in AI methods have created an unprecedented opportunity for building agile surveillance systems using the deluge of real-time data generated within a short span of time. During the COVID-19 pandemic, many reports have discussed the utility of AI approaches in prioritization, delivery, surveillance, and supply chain of drugs, vaccines, and non-pharmaceutical interventions. This review will discuss the clinical utility of AI-based models and will also discuss limitations and challenges faced by AI systems, such as model generalizability, explainability, and trust as pillars for real-life deployment in healthcare. View Full-Text
Keywords: COVID-19; machine learning; artificial intelligence; drug discovery; SARS-CoV-2; pandemic; diagnosis; prediction; surveillance; vaccine COVID-19; machine learning; artificial intelligence; drug discovery; SARS-CoV-2; pandemic; diagnosis; prediction; surveillance; vaccine
►▼ Show Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Supplementary Material

SciFeed

Share and Cite

MDPI and ACS Style

Arora, G.; Joshi, J.; Mandal, R.S.; Shrivastava, N.; Virmani, R.; Sethi, T. Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19. Pathogens 2021, 10, 1048. https://doi.org/10.3390/pathogens10081048

AMA Style

Arora G, Joshi J, Mandal RS, Shrivastava N, Virmani R, Sethi T. Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19. Pathogens. 2021; 10(8):1048. https://doi.org/10.3390/pathogens10081048

Chicago/Turabian Style

Arora, Gunjan, Jayadev Joshi, Rahul S. Mandal, Nitisha Shrivastava, Richa Virmani, and Tavpritesh Sethi. 2021. "Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19" Pathogens 10, no. 8: 1048. https://doi.org/10.3390/pathogens10081048

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Map by Country/Region

1
Back to TopTop