Healthcare Informatics for Fighting COVID-19 and Future Epidemics [E-Book] / edited by Lalit Garg, Chinmay Chakraborty, Saïd Mahmoudi, Victor S. Sohmen.
This book presents innovative solutions utilising informatics to deal with various issues related to the COVID-19 outbreak. The book offers a collection of contemporary research and development on the management of Covid-19 using health data analytics, information exchange, knowledge sharing, the In...
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Personal Name(s): | Chakraborty, Chinmay, editor |
Garg, Lalit, editor / Mahmoudi, Saïd, editor / Sohmen, Victor S., editor | |
Edition: |
1st edition 2022. |
Imprint: |
Cham :
Springer,
2022
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Physical Description: |
XIX, 438 pages 181 illustrations (online resource) |
Note: |
englisch |
ISBN: |
9783030727529 |
DOI: |
10.1007/978-3-030-72752-9 |
Series Title: |
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EAI/Springer Innovations in Communication and Computing
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Subject (LOC): |
- Introduction
- SECTION-1: Health Data Analytics and Mining for the COVID-19 pandemic
- COVID-19 pandemic big data analytics and application
- Artificial Intelligence approaches for the COVID-19 pandemic
- Machine learning and deep learning for the COVID-19 pandemic
- Cyber-Social Data Processing and Intelligence Mining for the COVID-19 pandemic
- Cloud-based Intelligent systems for the COVID-19 pandemic
- Smart hospital requirements for infectious diseases treatment
- Big data-driven health risk identification
- Pattern recognition in epidemic risk analysis
- Predictive modelling for the COVID-19 pandemic and future epidemics
- Image processing and computer vision for the COVID-19 pandemic
- Sentiment analysis for the COVID-19 pandemic
- Patient behaviour modelling for the COVID-19 pandemic
- Decision Support Systems (DSS) for the COVID-19 pandemic
- Disease outbreak and progression modelling and simulation for COVID-19 pandemic
- SECTION-2: Information exchange, knowledge sharing, data storage, and security for the COVID-19 pandemic
- COVID-19 information exchange
- Knowledge-sharing for the COVID-19 pandemic
- Blockchain for secured COVID-19 pandemic data handling
- Ontology-based models for the COVID-19 pandemic
- Cloud storage of the COVID-19 pandemic data
- Data warehousing for the COVID-19 pandemic
- Privacy and ethical issues for the COVID-19 pandemic information exchange and sharing
- Text mining and natural language processing for the COVID-19 pandemic
- Secure communication of the COVID-19 pandemic data
- Ensuring the integrity and reliability of the COVID-19 pandemic information
- Infodemic and fake news detection and its social spread prevention for the COVID-19 pandemic
- Data integrity, consistency, and compliance for the COVID-19 pandemic
- Health information impact assessment for the COVID-19 pandemic
- Secure handling and exchange of patient-generated data for the COVID-19 pandemic
- SECTION-3: The Internet of things (IoT) and the Internet ofEverything (IoE) for the COVID-19 pandemic
- Smart sensing for the COVID-19 pandemic
- Cloud-based secure IoT system for the COVID-19 pandemic
- Smart hospital for infectious diseases treatment
- Android Apps for the COVID-19 pandemic
- IoT and IoE application in microbial risk and healthcare
- Wireless sensor networks for the COVID-19 pandemic
- E-health, m-Health, and Telemedicine for the COVID-19 pandemic
- Wearable computing for the COVID-19 pandemic
- Hospital automation systems for the COVID-19 pandemic
- IoT and IoE based patient monitoring systems for the COVID-19 pandemic
- Security of IoT and IoE based data and devices for the COVID-19 pandemic
- IoT and IoE Hardware and software platforms for the COVID-19 pandemic
- Conclusion.