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In Wiley interdisciplinary reviews. Data mining and knowledge discovery

World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2. The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as deep learning, in (i) rapid disease detection from x-ray or computed tomography (CT) or high-resolution CT (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) forecasting the disease and psychological impact on the population from social networking data, and (iv) prediction of drug-protein interactions for repurposing the drugs, has attracted much attention. In the present study, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real-time polymerase chain reaction and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, prevent the spread of disease, and face mask detection are also discussed. We inspect how the virus transmits depending on different factors. We investigate the deep learning technique to assess the affinity of the most probable drugs to treat COVID-19. This article is categorized under:Application Areas > Health CareAlgorithmic Development > Biological Data MiningTechnologies > Machine Learning.

Dasgupta Abhijit, Bakshi Abhisek, Mukherjee Srijani, Das Kuntal, Talukdar Soumyajeet, Chatterjee Pratyayee, Mondal Sagnik, Das Puspita, Ghosh Subhrojit, Som Archisman, Roy Pritha, Kundu Rima, Sarkar Akash, Biswas Arnab, Paul Karnelia, Basak Sujit, Manna Krishnendu, Saha Chinmay, Mukhopadhyay Satinath, Bhattacharyya Nitai P, De Rajat K

EHR, deep learning, drug affinity, social media, x‐ray/CT/HRCT