4.7 Review

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

Journal

INTERNATIONAL JOURNAL OF BIOLOGICAL SCIENCES
Volume 17, Issue 6, Pages 1581-1587

Publisher

IVYSPRING INT PUBL
DOI: 10.7150/ijbs.58855

Keywords

Artificial intelligence; COVID-19; diagnosis; deep learning; machine learning

Funding

  1. Science and Technology Development Fund, Macau SAR [FDCT/0015/2018/A1, FDCT/126/2014/A3]
  2. National Key R&D Program of China [2019YFA0904400]
  3. Multi-Year Research Grant of University of Macau [MYRG201900069FHS, MYRG201600069FST]
  4. Guangzhou Science and Technology Innovation and Development of Special Funds [201807010004, EF003/FSTFSJ/2019/GSTIC, (EF004/FSTFSJ/2019/GSTI)]
  5. National Natural Science Foundation of China [31440041]
  6. Project of the Science and Technology Research Program of Chongqing Municipal Education Commission of China [KJQN202003601, KJZDK201903601]

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Artificial intelligence has been effectively utilized in various aspects of the COVID-19 crisis, accelerating the diagnosis of positive patients and providing guidance for ideal deployment in pandemics. Future applications of AI technology can help address current challenges and guide its optimal deployment in pandemics.
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.

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