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Leveraging Artificial Intelligence in Global Epidemics
Overview of the Book:
In the fight against epidemics, medical staff is on the front
line; but behind the lines the battle is
fought by the government officials, researchers, and data
scientists. Artificial Intelligence (AI) has
been helping nations with computer modeling and simulation for
predictions about e.g. the overall
economic situation, tax incomes and population development. In the
same manner, AI can prepare
the government for emergency situations by backing the medical
science. AI plays a key and cutting-edge
role in the preparedness for and dealing with the outbreak
situation of global epidemics. It can
help researchers analyze global data about known viruses to
predict the knows-hows of the next
pandemic and the impact it will have. Not only for prediction, but
also AI plays an increasingly
important role in assessing a country’s readiness, early
detection, identification of patients, generating
recommendations, situation awareness and more. It is up to the
right input and the innovative ways
by humans to leverage what AI can do.
As COVID-19 has grabbed the world and its economy today, an
analysis of the COVID-19
outbreak and the global responses and analytics will pay a long
way in preparing humanity for such
future situations. While there exist books about AI in various
application domains, what is currently
lacking is a book that provides a comprehensive coverage of
disease outbreak and specifically how AI
can help fight with epidemics. To fill this gap, this book
contains chapters describing the role AI
plays in various stages of a disease outbreak, with COVID-19 as a
case study.
Invitation to Contribute a Chapter:
The individual chapters should provide a comprehensive overview of
the chosen topic
covering advances in the area and should be tutorial in nature and
presentation, to
appeal to a broad range of readers who may NOT be researchers on
the topic. Hence,
they shouldn’t be like a research paper. You are hereby invited to
submit first, a 2-3 page
extended summary including (a) an abstract, (b) an outline / TOC /
list of headings and
sub-headings along with a summary of each heading, (c) short
biographies of the
authors, and (d) a statement why you are experts for the proposed
chapter. Following a
review of your summary, we’ll offer our feedback and suggestions
for improvement and
better synergy with rest of the chapters and cohesive coverage.
Chapter Submission Link:
https://easychair.orgconferences/?conf=aige2021
Structure of the Book:
The book is planned to have 11-12 chapters divided into two
sections. Part I consists of 3 chapters
providing a holistic overview of global epidemics, a motivation
for the book and challenges. Part II
consists of emerging technologies that help fight against
epidemics. Part II has 6 chapters as listed
below. This makes 9 chapters. The rest 2-3 chapters are to be
added dynamically based on the
availability of authors (These chapters may be on The Use of
Social Media for Tracking Public
Behavior, Does AI help in Genome Sequencing, AI-assisted Testing,
Computational Drug
Repurposing, or any other trending and suitable topic in line with
the title and the theme of the book).
Part I: Controlling Epidemics: A Perspective
This part provides an overview and study of Global Epidemic
situations. It starts with assessing
the countries' readiness for coping with epidemics, goes through
the challenges in battling with
epidemic, and then closes with a survey of existing approaches,
techniques and tools available or
developed by academicians or industry professionals for
controlling the epidemics.
1 Setting the Scene (A Chapter by the Editors)
This chapter provides an overview and summary of the complete book
as a whole It acts as glue
between the chapters written by different authors and brings in
synergy to all the chapters in both
the parts of the book. In effect, it sets the scene for the reader
and acts as an introductory and a
must read before proceeding for the further chapters.
2 An Overview of Global Epidemics and the Challenges Faced
(a) Assessing Countries’ Readiness for Coping with Epidemics:
There is a need of retrospective
evaluation of each country’s readiness for coping with epidemics.
An automated data collection
followed by evaluation will help in knowing if the human kind is
well-equipped to deal with it.
(b) A Study related to Ebola, Corona viruses, Zika, influenza,
Dengue, Chikungunya, Malaria like
infectious diseases will be presented in this chapter. A
discussion on the most fatal pandemics
recorded in the history (like the Plague, Spanish Flu, HIV/AIDS,
COVID-19) and their economic
consequences. What is common in these? All these have jumped to
humans after being originated
in animals somehow.
(c) Challenges in Battling with Epidemics
(d) …
…
3 A Survey of Existing Approaches and Tools to fight against
epidemic and the lessons learnt
(a) Survey of tools/techniques/methodologies/software already
available at the time of writing of
this book to predict/detect/recommend actions during an epidemic
situation.
(b) Lessons learnt by every epidemic that has struck this world
(including COVID-19)
Part II: Emerging Technologies Fight Against Epidemics
Having gone through the background of controlling global epidemic
situation, this part of the
book covers the emerging techniques to fight against epidemic. A
number of digital
technologies……………This book focuses on …”Artificial Intelligence”….
At the time of writing this book, COVID-19 pandemic was caused by
coronavirus and was
widespread with deadly results. The case study of COVID-19 has
been presented to better exploit
the study presented in each chapter.
…
4 AI Technologies specialized to the need in the fight against
epidemic
All current technologies under the umbrella of AI or surrounding
AI should be covered like Data
Science, Big Data, Machine Learning, Semantic Technologies, Data
Analytics, cyber security.
5 Does AI help in Forecasting?
This chapter will speak about WHO statistics on pathogens. AI can
help predicting everything
about spillovers, hence allowing the governments to plan ahead. AI
can predict what, when, why,
and where of the epidemic. We define AI and discuss the various
machine learning models to
predict the same.
Case Study of Covid-19 for Predictions will be presented.
6 AI and Detection / Improved Diagnosis
In case of outbreak of a disease; after detection, we need to
publicize the threat. AI makes possible
quick detection in order to enable possible vaccination and
treatment; and alerts for the public.
Diagnosis and Monitoring of cases is of paramount importance.
Case Study of Covid-19 for Early Detection will be presented.
7 Generating Recommendations
A global, AI-enabled data system can provide advices and issue
warnings in real time. Help
manage socio-economic impacts.
8 Role of AI in Contact Tracing
The architecture of so called “Corona apps” and their backends is
described in this chapter. The
role of AI is clarified for these approaches and also other
aspects like privacy and security.
Furthermore, other approaches to contact tracing are introduced in
this chapter.
9 Situation Awareness
In any disaster, it is essential that the citizens get the correct
information and organizations get the
correct data. This chapter describes AI approaches to detect fake
news or scams.
….
10-12 Open Topics dynamically picked by the authors
Any other trending and suitable topic in line with the title and
the theme of the book can be
incorporated.
Editors:
- Le Gruenwald, The University of Oklahoma, USA,
ggruenwald@ou.edu
- Sarika Jain, National Institute of Technology, Kurukshetra,
Haryana, India,
jasarika@nitkkr.ac.in.
- Sven Groppe, University of Lübeck, Germany,
groppe@ifis.uni-luebeck.de
Deadlines:
Extended Summary: Sep 30, 2020
Notification of Proposal Approval: Oct 20, 2020
Full Chapter Submission: Jan 10, 2020
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