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Intelligent Systems and Methods to Combat Covid-19 [electronic resource] /

Contributor(s): Material type: TextTextSeries: SpringerBriefs in Computational IntelligencePublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2020Edition: 1st ed. 2020Description: XII, 91 p. 21 illus., 18 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789811565724
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q342
Online resources:
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.
In: Springer Nature eBookSummary: 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.
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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.

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.

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