id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-344252-6g3zzj0o	Farooq, Junaid	A Novel Adaptive Deep Learning Model of Covid-19 with focus on mortality reduction strategies	2020-07-21		.txt	text/plain	6951	361	56	We employ deep learning to propose an Artificial Neural Network (ANN) based and data stream guided real-time incremental learning algorithm for parameter estimation of a non-intrusive, intelligent, adaptive and online analytical model of Covid-19 disease. In this work, we employ deep learning to propose an Artificial Neural Network (ANN) based real-time online incremental learning technique to estimate parameters of a data stream guided analytical model of Covid-19 to study the transmission dynamics and prevention mechanism for SARS-Cov-2 novel coronavirus in order to aid in optimal policy formulation, efficient decision making, forecasting and simulation. To the best of our knowledge, this paper develops for the first time a deep learning model of epidemic diseases with data science approach in which parameters are intelligently adapted to the new ground realities with fast evolving infection dynamics.	./cache/cord-344252-6g3zzj0o.txt	./txt/cord-344252-6g3zzj0o.txt