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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 27, 2020
Date Accepted: Jul 29, 2020
Date Submitted to PubMed: Dec 7, 2020

The final, peer-reviewed published version of this preprint can be found here:

Artificial Intelligence in the Fight Against COVID-19: Scoping Review

Abd-Alrazaq A, Alajlani M, Alhuwail D, Schneider J, Al-Kuwari S, Shah Z, Hamdi M, Househ M

Artificial Intelligence in the Fight Against COVID-19: Scoping Review

J Med Internet Res 2020;22(12):e20756

DOI: 10.2196/20756

PMID: 33284779

PMCID: 7744141

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Artificial Intelligence in the Fight against COVID-19: A Scoping Review

  • Alaa Abd-Alrazaq; 
  • Mohannad Alajlani; 
  • Dari Alhuwail; 
  • Jens Schneider; 
  • Saif Al-Kuwari; 
  • Zubair Shah; 
  • Mounir Hamdi; 
  • Mowafa Househ

ABSTRACT

Background:

In December 2019, the novel Coronavirus disease (COVID-19) broke out in Wuhan, China leading to major national and international disruptions in healthcare, business, education, transportation, and nearly every aspect of our daily lives. Artificial Intelligence (AI) has been leveraged amid the COVID-19 pandemic, however, little is known about its use for supporting public health efforts.

Objective:

The scoping review aimed to explore how AI technology is being used during the COVID-19 pandemic, as reported in the literature. Thus, it is first review that describes and summarizes features of the identified AI techniques and datasets used for their development and validation.

Methods:

A scoping review was conducted following the guidelines of PRISMA Extension for Scoping Reviews (PRISMA-ScR). We searched the most commonly used electronic databases (e.g., MEDLINE, EMBASE, PsycInfo) between April 10 and 12, 2020. These terms were selected based on the target intervention (i.e., AI) and the target disease (i.e., COVID-19). Two reviewers independently conducted study selection and data extraction. A narrative approach was used to synthesize the extracted data.

Results:

We considered 82 studies out of the 435 retrieved studies. The most common use of AI was diagnosing COVID-19 cases based on various indicators. AI was also employed in drug and vaccine discovery or repurposing, and assessing their safety. Further, the included studies used AI for forecasting the epidemic development of COVID-19 and predicting its potential hosts/reservoirs. Researchers utilized AI for patient outcome-related tasks such as assessing the severity of COVID-19, predicting mortality risk, its associated factors, and length of hospital stay. AI was used for Infodemiology to raise awareness to use water, sanitation, and hygiene. The most prominent AI techniques used were Convolutional Neural Network (CNN) followed by Support Vector Machine (SVM).

Conclusions:

The included studies showed that AI has the potential to fight against COVID-19. However, many of the proposed methods are not yet clinically accepted. Thus, the most rewarding research will be on methods promising value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for studies on AI.


 Citation

Please cite as:

Abd-Alrazaq A, Alajlani M, Alhuwail D, Schneider J, Al-Kuwari S, Shah Z, Hamdi M, Househ M

Artificial Intelligence in the Fight Against COVID-19: Scoping Review

J Med Internet Res 2020;22(12):e20756

DOI: 10.2196/20756

PMID: 33284779

PMCID: 7744141

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