• Sana Khan
• Prof. Zuber Farooqui

In 2020, the world has been hit by a global pandemic of COVID-19, belonging to the family of Coronavirus. Due to the rapid increase in the infection and the death rate, people have started to develop mixed feelings regarding this situation. This paper proposed a deep learning method to predict the seriousness of the decrease in COVID-19 infected patient. Using this novel method, the proposed model can both take in a large number of heterogeneous features, such as census data, intra-county mobility, inter-county mobility, social distancing data, past growth of infection, among others, and learn complex interactions between these features. Simulation is performed using python sypder 3.7 software. The simulated results shows that the 77.5% accuracy to detection of covid-19. Precision, recall and Fmeasure values is also optimized and its gives significant better performance.

Covid-19, Machine Learning, Deep learning, Artificial Intelligence, Python

"An Adaptive Approach based on Machine Learning for Covid-19 Diagnosis and Prediction using Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 12, page no.f405-f410, December-2021, Available :http://www.jetir.org/papers/JETIR2112552.pdf

"An Adaptive Approach based on Machine Learning for Covid-19 Diagnosis and Prediction using Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 12, page no. ppf405-f410, December-2021, Available at : http://www.jetir.org/papers/JETIR2112552.pdf