Binding: Hardcover
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.
Title: Data Analytics For Pandemics A Covid - 19 Case Study
Author(s): Dey Nilanjan (Jis University Kolkata)
Publisher: Taylor & Francis Ltd
Barcode: 9780367558468
Pages: 68 Pages, 1 Tables, Black And White; 9 Illustrations, Black And White
Publication Date: 8/31/2020
Series: Intelligent Signal Processing and Data Analysis
Category: Computer Science