RESEARCH AND APPLICATION ADVANCES OF ARTIFICIAL INTELLIGENCE IN DIAGNOSIS AND EPIDEMIC PREDICTION OF COVID-19

Jinping Liu (), Juanjuan Wu (), Subo Gong (), Waiguang Hu, Ying Zhou () and Shanshan Hu ()
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Jinping Liu: College of Information Science and Engineering, Hunan Normal University, Changsha 410081, P. R. China
Juanjuan Wu: College of Information Science and Engineering, Hunan Normal University, Changsha 410081, P. R. China
Subo Gong: Department of Geriatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, P. R. China
Waiguang Hu: Data Information Management Center, Hunan Children’s Hospital, Changsha 410007, P. R. China
Ying Zhou: Data Information Management Center, Hunan Children’s Hospital, Changsha 410007, P. R. China
Shanshan Hu: Data Information Management Center, Hunan Children’s Hospital, Changsha 410007, P. R. China

FRACTALS (fractals), 2023, vol. 31, issue 06, 1-36

Abstract: COVID-19 is a dangerous disease that directly damages human health, with the properties of severely contagious and highly variable. It is endangering the health and safety of people all around the world. Thus, it compels governments to seek rapid detection, diagnosis and treatment, and epidemic forecasting approaches under the consumption of considerable human resources, material, and financial resources, for the purpose of curbing its development. In view of diverse merits, such as flexibility, rapidity, and non-intrusion, artificial intelligence (AI) techniques have unparalleled advantages in the rapid, non-contact auxiliary diagnosis and epidemic prediction of COVID-19. This paper reviews the AI’s technical advances and clinical applications in the COVID-19 epidemic, including computer-aided diagnosis and epidemic prediction, especially the pipelines of medical imaging and analytical techniques. The survey aims to comprehensively investigate the application of AI technologies in the fight against the epidemic and attempt to organize related works in a globally understandable way. This survey also summarizes current challenging issues in the diagnosis and prediction of COVID-19 with AI technologies and puts forward some suggestions for future work.

Keywords: COVID-19; Artificial Intelligence; Computer-Aided Diagnosis; Epidemic Trend Forecasting (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0218348X23401084

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