Int J Biol Sci 2021; 17(6):1581-1587. doi:10.7150/ijbs.58855

Review

Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives

Shigao Huang1#, Jie Yang2,3#, Simon Fong2✉, Qi Zhao1✉

1. Cancer Centre, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau 999078, Macau SAR, China.
2. Department of Computer and Information Science, University of Macau 999078, Macau SAR, China.
3. Chongqing Industry & Trade Polytechnic 408000, Chongqing, China.
# Shigao Huang and Jie Yang contributed equally to this work

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Citation:
Huang S, Yang J, Fong S, Zhao Q. Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives. Int J Biol Sci 2021; 17(6):1581-1587. doi:10.7150/ijbs.58855. Available from https://www.ijbs.com/v17p1581.htm

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Abstract

Artificial intelligence (AI) is being used to aid in various aspects of the COVID-19 crisis, including epidemiology, molecular research and drug development, medical diagnosis and treatment, and socioeconomics. The association of AI and COVID-19 can accelerate to rapidly diagnose positive patients. To learn the dynamics of a pandemic with relevance to AI, we search the literature using the different academic databases (PubMed, PubMed Central, Scopus, Google Scholar) and preprint servers (bioRxiv, medRxiv, arXiv). In the present review, we address the clinical applications of machine learning and deep learning, including clinical characteristics, electronic medical records, medical images (CT, X-ray, ultrasound images, etc.) in the COVID-19 diagnosis. The current challenges and future perspectives provided in this review can be used to direct an ideal deployment of AI technology in a pandemic.

Keywords: Artificial intelligence, COVID-19, diagnosis, deep learning, machine learning