Welcome to the homepage of Dr. Lalit Garg
  • Home
  • Appointments
  • Qualifications
  • Research interest
  • Publications
  • Projects
  • Supervisions
  • Software
  • Other Activities
  • Interesting Links
  • Contact me
  • Call for Articles
  • ISMS2020 Program
  • ISMS2020 Detailed Program
Picture

Call for Chapters

Intelligent Healthcare Informatics for Fighting the COVID-19 and Other Pandemics and Epidemics

Deadlines
Chapter Proposal Submission : May 29, 2020
Abstract Submission : June 30, 2020 
Full Chapter Submission: July 31, 2020

Editors

Dr. Lalit Garg – University of Malta, Msida, Malta
Dr. Chinmay Chakraborty – Birla Institute of Technology, Mesra, India
Prof. Saïd Mahmoudi – University of Mons, Belgium
Prof. Victor S. Sohmen – Harrisburg University of Science and Technology, USA

Scope










​
​

Topics
















































































​

How to submit



















Contact

The COVID-19 outbreak is among the most significant tragedies the world has ever faced. It has already killed hundreds of thousands of people; millions of people are infected, billions of people are in lockdown, and this is costing trillions of USDs to the world economy. Intelligent healthcare informatics can play a vital role in this challenging time. The objective of the book is to present innovative solutions utilising informatics to deal with various issues related to the COVID-19 outbreak including health data analytics, information exchange, knowledge sharing, Internet of Things (IoT)-based solutions, the implementation, assessment, adoption, and management of healthcare informatics solutions.
​
  • 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
  • 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, fake news detection and its social spread prevention
  • 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
  • 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
  • Healthcare Technology Assessment, adoption and management for COVID-19
  • Health information systems testing and maintenance for COVID-19
  • Healthcare Technology Infrastructure for COVID-19
  • User behaviour modelling for COVID-19
  • The clinical challenges for COVID-19
  • Global supply chains for healthcare emergencies
  • Risk of global economic COVID-19 costs
  • Management of future outbreaks risks (prevention, control, and treatment),
  • Interdisciplinary approaches and decision-making tools in microbial and healthcare risk
  • Cost-effective and efficient delivery solutions for COVID-19
  • Consumer Health Informatics for COVID-19
  • User perspectives for information systems and devices for COVID-19
  • Future pandemic or epidemic preparedness models and simulation
Abstracts should be submitted as plain Word (2010 or higher) or PDF files by e-mail to lalit.garg@um.edu.mt.
The abstract should contain:
  • Title of the proposed chapter
  • Author(s) of the chapter (including affiliation) 
  • Type of contribution (case study, full research paper or conceptual paper)
  • Estimated amounts of pages (excl. references)
  • Abstract of 500 words describing contents of the book chapter (incl. methodology)
  • Keywords (at least 2 and maximum of 5)
Full book chapters will also be submitted through e-mail to lalit.garg@um.edu.mt.  Full book chapters need to be formatted according the Springer instructions and submitted in Word (2010 or higher) or PDF format. These formatting instructions will be e-mailed together with the acceptance notification of your abstract

For further questions, please contact Dr Lalit Garg (lalit.garg@um.edu.mt). 
Powered by Create your own unique website with customizable templates.