NDLI: Data Analytics for Pandemics

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Data Analytics for Pandemics

Content Provider	Scilit
Author	Shinde, Gitanjali Rahul Kalamkar, Asmita Balasaheb Mahalle, Parikshit N. Dey, Nilanjan
Copyright Year	2020
Description	Epidemic trend analysis, timeline progression, prediction, and recommendation are critical for initiating effective public health control strategies, and AI and data analytics play an important role in epidemiology, diagnostic, and clinical fronts. The focus of this book is data analytics for COVID-19, which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussions on data models, their performance, different big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies. Aimed at Data Analysts, Epidemiologists and associated researchers, this book: discusses challenges of AI model for big data analytics in pandemic scenarios; explains how different big data analytics techniques can be implemented; provides a set of recommendations to minimize infection rate of COVID-19; summarizes various techniques of data processing and knowledge extraction; enables users to understand big data analytics techniques required for prediction purposes.
Related Links	https://content.taylorfrancis.com/books/download?dac=C2020-0-16212-5&isbn=9781003095415&format=googlePreviewPdf
DOI	10.1201/9781003095415
Language	English
Publisher	Informa UK Limited
Publisher Date	2020-08-30
Access Restriction	Open
Subject Keyword	Book Name: Data Analytics for Pandemics Information Systems Models Recommendation Scenarios Analytics in Pandemic
Content Type	Text
Resource Type	Book

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