UID:
almahu_9949890968502882
Umfang:
1 online resource (xv, 68 pages) :
,
illustrations.
Ausgabe:
First edition.
ISBN:
9781000204414
,
1000204413
,
9781003095415
,
1003095410
,
9781000204452
,
1000204456
Serie:
CRC focus series
Inhalt:
"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 discussion 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"--
Anmerkung:
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgment -- Authors -- Chapter 1 COVID-19 Outbreak -- 1.1 Introduction -- 1.2 Epidemic and Pandemic Overview -- 1.2.1 Stages of Disease -- 1.2.2 Pandemic Phases -- 1.2.2.1 Pandemic Risk Factors -- 1.2.2.2 Pandemic Mitigation -- 1.2.2.3 Situational Awareness -- 1.2.2.4 History of Pandemics -- 1.3 Novel Coronavirus -- 1.4 Medical Overview -- Nature and Spread -- 1.5 Vulnerability Index -- References -- Chapter 2 Data Processing and Knowledge Extraction -- 2.1 Data Sources and Related Challenges -- 2.2 Data Storage: Platform -- 2.2.1 Storage Services -- 2.2.2 Big Data Analytics Services -- 2.2.3 Data Warehousing Services -- 2.3 Data Processing -- 2.3.1 Missing Values Imputation -- 2.3.2 Noise Treatment -- 2.4 Knowledge Extraction -- 2.4.1 Knowledge Extraction Based on Data Types -- 2.4.1.1 Knowledge Extraction from Text Data -- 2.4.1.2 Knowledge Extraction from Image Data -- 2.4.1.3 Knowledge Extraction from Audio Data -- 2.4.1.4 Knowledge Extraction from Video Data -- 2.4.2 Knowledge Extraction Techniques -- References -- Chapter 3 Big Data Analytics for COVID-19 -- 3.1 All You Need to Know -- 3.1.1 WEB 2.0 -- 3.1.2 Critical Thinking -- 3.1.3 Statistical Programming (R/Python) -- 3.1.4 R Programming Language -- 3.1.5 Python Programming Language -- 3.2 Data Visualization -- 3.2.1 Big Data Analytics and COVID-19 -- 3.2.1.1 Statistical Parameters -- 3.2.1.2 Predictive Analytics -- 3.3 Data Models and Performance -- 3.3.1 Data Modeling Phases -- 3.3.2 Ensemble Data Model -- 3.3.3 Model Performance -- 3.4 Big Data Techniques -- 3.4.1 Association Rule Learning -- 3.4.2 Classification Tree Analysis -- 3.4.3 Genetic Algorithm -- 3.4.4 Machine Learning -- 3.4.5 Regression Analysis -- 3.4.6 Social Network Analysis -- 3.5 Big Data Tools and Technology.
Weitere Ausg.:
Print version: Shinde, Gitanjali Rahul, 1983- Data analytics for coronavirus disease (COVID-19) outbreak Boca Raton, FL : CRC Press, 2021. ISBN 9780367558468
Sprache:
Englisch
URL:
https://www.taylorfrancis.com/books/9781003095415
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