Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives |
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| Authors: | Shigao Huang Jie Yang Simon Fong Qi Zhao |
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| Affiliation: | 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. |
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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. |
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| Keywords: | Artificial intelligence COVID-19 diagnosis deep learning machine learning |
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