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| Bimonthly Since 1986 |
ISSN 1004-9037
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| Publication Details |
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
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Abstract
The virus that causes Covid-19 is quickly spreading around the globe. Approximately every three to four times, waves are created that have a significant effect on people's lives. It's unclear if this situation involves a lack of effective identification of covid illnesses or any other illness. There is no reliable statistics on the total number of covid patients in the nation, and no system exists to track them. This prevents people from receiving necessary care and services. The number of patients in a given dataset may be determined with more precision using AI methods. In this study, we provide an adjustable method for anticipating the number of patients in Covid-19. A piece of software called python spyder is used to run the simulation.
Keyword
Covid, Patient, prediction, dataset, Artificial intelligence.
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