Dasgupta, A.; Bakshi, A.; Mukherjee, S.; Das, K.; Talukdar, S.; Chatterjee, P.; Mondal, S.; Das, P.; Ghosh, S.; Som, A.; et al. Epidemiological Challenges in Pandemic Coronavirus Disease (
COVID ‐19): Role of Artificial Intelligence. WIREs Data Mining and Knowledge Discovery 2022, 12, doi:10.1002/widm.1462.
Dasgupta, A.; Bakshi, A.; Mukherjee, S.; Das, K.; Talukdar, S.; Chatterjee, P.; Mondal, S.; Das, P.; Ghosh, S.; Som, A.; et al. Epidemiological Challenges in Pandemic Coronavirus Disease (
COVID ‐19): Role of Artificial Intelligence. WIREs Data Mining and Knowledge Discovery 2022, 12, doi:10.1002/widm.1462.
Dasgupta, A.; Bakshi, A.; Mukherjee, S.; Das, K.; Talukdar, S.; Chatterjee, P.; Mondal, S.; Das, P.; Ghosh, S.; Som, A.; et al. Epidemiological Challenges in Pandemic Coronavirus Disease (
COVID ‐19): Role of Artificial Intelligence. WIREs Data Mining and Knowledge Discovery 2022, 12, doi:10.1002/widm.1462.
Dasgupta, A.; Bakshi, A.; Mukherjee, S.; Das, K.; Talukdar, S.; Chatterjee, P.; Mondal, S.; Das, P.; Ghosh, S.; Som, A.; et al. Epidemiological Challenges in Pandemic Coronavirus Disease (
COVID ‐19): Role of Artificial Intelligence. WIREs Data Mining and Knowledge Discovery 2022, 12, doi:10.1002/widm.1462.
Abstract
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 (SARS-CoV- 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/computerized tomography (CT)/ high-resolution computed tomography (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) identification of the epicenter in each country/state and forecasting the disease from social networking data, (iv) prediction of drug-protein interactions for repurposing the drugs, and (v) socio-economic impact and prediction of future relapses, has attracted much attention. In the present manuscript, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real time polymerase chain reaction (qRT-PCR) and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, possibility of future relapses and socio-economic impact are also discussed. We inspect how the virus transmits depending on different factors, such as, population density and mobility among others. We depict how AI-based mobile app for contact tracing and surveys can prevent the transmission. A modified deep learning technique can assess affinity of the most probable drugs to treat COVID-19. Here a few effective antiviral drugs, such as, Geneticin, Avermectin B1, and Ancriviroc among others, have been reported with their appropriate validation from previous investigations.
Keywords
SIRD; Twitter; GHSI; Pre-symptomatic; EHR; Contact tracing; On-line survey; qRT-PCR; X-ray; CT/HRCT; CNN; Autoencoder; Drug affinity; CPI; and Inflation.
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received:
14 May 2020
The commenter has declared there is no conflict of interests.
Comment:
The article has a crucial input about the role of Artificial intelligence to fight against the disease. I express my sincere gratitude to the authors to raise such issues through there research. However, significant drug design may requires in vitro studies in the near future.
Received:
15 May 2020
The commenter has declared there is no conflict of interests.
Comment:
An interesting paper. I am impressed with this kind of intriguing work using artificial intelligence. It will pave a future path to predict the drug for repurposing and validation.
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The commenter has declared there is no conflict of interests.
The commenter has declared there is no conflict of interests.
Commenter: Sourajit Sarkar
The commenter has declared there is no conflict of interests.
The commenter has declared there is no conflict of interests.
The commenter has declared there is no conflict of interests.