RETRACTED: Analytical study on COVID-19 to predict future infected cases ratio in India using Machine Leaning

Abstract

COVID-19 is real a worldwide terrific problem. This paper focuses on the different aspects of data analytics and visualization by using various datasets supported by authorized sources. It also discusses the practical aspects using open source tools and python library support. Here chapter focuses on comparative analysis also. It also visualize analytical aspects by different aspects such as country wise, date wise and so on. In this paper, the COVID infected cases and its reaction on people will be discussed. This case study will predict the COVID-19 infected cases and death ratio with symptoms in future. This paper focus on data visualization, data analytics and comparative study based on practical aspects. Machine Learning plays a vital role to predict the cases by providing learning instances.

Managing SARS-CoV-2 Testing in Schools with an Artificial Intelligence Model and Application Developed by Simulation Data

“…These challenges have resorted data intensive modeling [6] and computational intelligence methods [7] that embrace the complexity of the issues that arise from the pandemic, from lack of human resources [8] and data resources [9,10], to the lack of emergency preparedness and capabilities to respond effectively [11]. An increasing amount of studies set out to explore models and artifacts that leverage artificial intelligence (AI) methods and methodologies to explore pandemic facts and circumstances from several differing yet often complementary angles, from the composites and overarching description of the virus itself [12], to diseases detection and diagnosis [13,14] to prediction on infection rates [15], patient management [16], the protection of healthcare workers [17,18], as well as hygiene measures, prevention and containment [19], drug development [20], and treatment [21][22][23]. The use of AI techniques is perceived to be a paradigm shift [24] towards approaches that use data science in empowering ways to craft, test and deploy public health care policies [25,26].…”