European Parliament Library

Enabling healthcare 4. 0 for pandemics, a roadmap using AI, machine learning, IoT and cognitive technologies, edited by Abhinav Juneja [and four others]

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Summary
ENABLING HEALTHCARE 4.0 for PANDEMICS The book explores the role and scope of AI, machine learning and other current technologies to handle pandemics. In this timely book, the editors explore the current state of practice in Healthcare 4.0 and provide a roadmap for harnessing artificial intelligence, machine learning, and Internet of Things, as well as other modern cognitive technologies, to aid in dealing with the various aspects of an emergency pandemic outbreak. There is a need to improvise healthcare systems with the intervention of modern computing and data management platforms to increase the reliability of human processes and life expectancy. There is an urgent need to come up with smart IoT-based systems which can aid in the detection, prevention and cure of these pandemics with more precision. There are a lot of challenges to overcome but this book proposes a new approach to organize the technological warfare for tackling future pandemics. In this book, the reader will find: State-of-the-art technological advancements in pandemic management; AI and ML-based identification and forecasting of pandemic spread; Smart IoT-based ecosystem for pandemic scenario. Audience The book will be used by researchers and practitioners in computer science, artificial intelligence, bioinformatics, data scientists, biomedical statisticians, as well as industry professionals in disaster and pandemic management
Table of contents
Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1: MACHINE LEARNING FOR HANDLINGCOVID-19 -- 1 COVID-19 and Machine Learning Approaches to Deal With the Pandemic -- 1.1 Introduction -- 1.1.1 COVID-19 and its Various Transmission Stages Depending Upon the Severity of the Problem -- 1.2 COVID-19 Diagnosis in Patients Using Machine Learning -- 1.2.1 Machine Learning to Identify the People who are at More Risk of COVID-19 -- 1.2.2 Machine Learning to Speed Up Drug Development -- 1.2.3 Machine Learning for Re-Use of Existing Drugs in Treating COVID-19 -- 1.3 AI and Machine Learning as a Support System for Robotic System and Drones -- 1.3.1 AI-Based Location Tracking of COVID-19 Patients -- 1.3.2 Increased Number of Screenings Using AI Approach -- 1.3.3 Artificial Intelligence in Management of Resources During COVID-19 -- 1.3.4 Influence of AI on Manufacturing Industry During COVID-19 -- 1.3.5 Artificial Intelligence and Mental Health in COVID-19 -- 1.3.6 Can AI Replace the Human Brain Intelligence in COVID-19 Crisis? -- 1.3.7 Advantages and Disadvantages of AI in Post COVID Era -- 1.4 Conclusion -- References -- 2 Healthcare System 4.0 Perspectives on COVID-19 Pandemic -- 2.1 Introduction -- 2.2 Key Techniques of HCS 4.0 for COVID-19 -- 2.2.1 Artificial Intelligence (AI) -- 2.2.2 The Internet of Things (IoT) -- 2.2.3 Big Data -- 2.2.4 Virtual Reality (VR) -- 2.2.5 Holography -- 2.2.6 Cloud Computing -- 2.2.7 Autonomous Robots -- 2.2.8 3D Scanning -- 2.2.9 3D Printing Technology -- 2.2.10 Biosensors -- 2.3 Real World Applications of HCS 4.0 for COVID-19 -- 2.4 Opportunities and Limitations -- 2.5 Future Perspectives -- 2.6 Conclusion -- References -- 3 Analysis and Prediction on COVID-19 Using Machine Learning Techniques -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Types of Machine Learning
Language
eng
Literary form
non fiction
Note
Includes index
Physical description
1 online resource (352 pages)
Specific material designation
remote
Form of item
online
ISBN
9781119769088

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