Healthcare informatics for fighting COVID-19 and future epidemics

Healthcare informatics for fighting COVID-19 and future epidemics / Lalit Garg, Chinmay Chakraborty, Saïd Mahmoudi, Victor S. Sohmen, editors.

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...

Full description

Saved in:
Bibliographic Details
Other Authors: Garg, Lalit, 1977- (Editor), Chakraborty, Chinmay, 1984- (Editor), Mahmoudi, Saïd (Editor), Sohmen, Victor S. (Editor)
Format: eBook
Language:English
Published: Cham : Springer, [2022]
Series:EAI/Springer innovations in communication and computing.
Subjects:
Since 2020
Medical informatics.
COVID-19 Pandemic, 2020- > Data processing.
Electronic data processing
Medical informatics
Online Access:Click for online access
Table of Contents:
  • 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 of Everything (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.

Similar Items