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Review
. 2021 Apr 10;17(6):1581-1587.
doi: 10.7150/ijbs.58855. eCollection 2021.

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

Shigao Huang  1 , Jie Yang  2   3 , Simon Fong  2 , Qi Zhao  1
Affiliations
Review

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

Shigao Huang et al. Int J Biol Sci. .

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; deep learning; diagnosis; machine learning.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
A flowchart of the artificial intelligence methods for COVID-19 diagnosis: machine learning and deep learning were applied in the medical characteristic to diagnosis the COVID-19 infection.
See this image and copyright information in PMC

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