Optimal control strategy for COVID-19 developed using an AI-based learning method

The corona virus pandemic has affected millions of people's work and communication. Millions face a health crisis from SARS-CoV-2, the virus that causes most COVID-19 symptoms. The aim of the proposed research is to contribute towards AI (Artificial Intelligence) by developing a mathematical model for SEIR and SIR through CNN on images of affected people and to analyse the dataset of medical images and healthcare outbreaks from 2019 to 2022 to provide an efficient COVID-19 diagnosis tool. The proposed research uses AI and mathematical modelling to develop a learning platform that analyzes images of affected people using CNN to diagnose COVID-19. The dataset used in this research includes medical images and healthcare outbreaks from 2019 to 2022, which are analysed through the SEIR and SIR mathematical models to provide an efficient and accurate COVID-19 diagnosis tool. The results of this research show that the proposed AI learning method is effective in diagnosing COVID-19 using images of affected individuals. The mathematical model for SEIR and SIR, analysed through CNN, provides accurate and efficient diagnosis of COVID-19. The dataset used in this research also provides valuable insights into the outbreak of COVID-19 and its impact on healthcare systems.

Automated summary

The corona virus pandemic has affected millions of people's work and communication. The proposed research aims to develop a mathematical model for SEIR and SIR through CNN analysis on images of affected people, providing an efficient COVID-19 diagnosis tool.