Intelligent systems and methods to combat Covid-19
- Responsibility
- Amit Joshi, Nilanjan Dey, K.C. Santosh, editors.
- Digital
- text file
- Publication
- Singapore : Springer, [2020]
- Physical description
- 1 online resource
- Series
- SpringerBriefs in applied sciences and technology. Computational intelligence.
Online
Available online
More options
Description
Creators/Contributors
- Contributor
- Joshi, Amit, editor.
- Dey, Nilanjan, 1984- editor.
- Santosh, K. C., editor.
Contents/Summary
- Bibliography
- Includes bibliographical references.
- Contents
-
- Chapter 1. Data Analytics: COVID-19 Prediction using Multimodal Data.-
- Chapter 2. COVID-19 Apps: Privacy and security concerns.-
- Chapter 3. Coronavirus Outbreak: Multi-objective Prediction and Optimization.-
- Chapter 4. AI-Enabled Framework to Prevent COVID-19 from Further Spreading.-
- Chapter 5. Artificial Intelligence Enabled Robotic Drones for COVID-19 Outbreak.-
- Chapter 6. Understanding and Analysis of Enhanced COVID-19 Chest X-Ray Images.-
- Chapter 7. Deep Learning-based COVID-19 Diagnosis and Trend Predictions.-
- Chapter 8. COVID-19: Loose Ends.-
- Chapter 9. Social Distancing and Artificial Intelligence- Understanding the Duality in the times of Covid-19.-
- Chapter 10. Post Covid-19 and Business Analytics.
- (source: Nielsen Book Data)
- Publisher's summary
-
This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.
(source: Nielsen Book Data)
Subjects
- Subjects
- COVID-19 (Disease) > Data processing.
- Artificial intelligence > Medical applications.
- COVID-19 > Informatique.
- Intelligence artificielle en médecine.
- Artificial intelligence.
- Health & safety aspects of IT.
- Automatic control engineering.
- Databases.
- Computers > Intelligence (AI) & Semantics.
- Medical > General.
- Technology & Engineering > Automation.
- Computers > Database Management > General.
- Technology & Engineering > Engineering (General)
- Artificial intelligence > Medical applications
Bibliographic information
- Publication date
- 2020
- Series
- SpringerBriefs in Applied Sciences and Technology. Computational Intelligence
- ISBN
- 9789811565724 (electronic bk.)
- 9811565724 (electronic bk.)
- 9811565716
- 9789811565717
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