-------- Forwarded Message --------
*Call for Book Chapters for the Springer-Verlag Handbook:***
*“Intelligent Technologies for Healthcare Business
Applications”***
* (Indexed by Scopus)*
*/Editors/*
*Athina Bourdena, Hellenic Mediterranean University, Greece*
*Constandinos X. Mavromoustakis, University of Nicosia, Cyprus*
*Evangelos K. Markakis, Hellenic Mediterranean University, Greece*
*George Mastorakis, Hellenic Mediterranean University, Greece*
*Evangelos Pallis, University of West Attica, Greece*
**
The healthcare industry has long been at the forefront of
innovation and technological advancement, and intelligent
technologies have the potential to revolutionize the way
healthcare businesses operate. From improving patient outcomes to
streamlining administrative processes, intelligent technologies
can offer a range of benefits to healthcare businesses. One of the
most promising areas for intelligent technologies in healthcare is
in the field of predictive analytics. Predictive analytics uses
data mining, machine learning, and other advanced analytics
techniques to identify patterns and relationships in large data
sets. By analyzing patient data, healthcare businesses can
identify trends and risk factors that can help them to predict and
prevent health problems before they occur. For example, predictive
analytics can be used to identify patients who are at high risk of
developing a particular disease or condition, and to provide
targeted interventions to prevent the condition from developing.
Another promising area for intelligent technologies in healthcare
is in the field of telehealth (telemedicine). Telehealth allows
healthcare professionals to provide remote care to patients, using
video conferencing, remote monitoring devices, and other
technologies. Telehealth can help to improve access to healthcare,
particularly for patients in rural or remote areas, and can also
help to reduce healthcare costs by minimizing the need for
in-person visits. Intelligent technologies such as machine
learning and natural language processing can be used to analyze
patient data collected through telehealth visits, and to provide
personalized recommendations for care.
Intelligent technologies can also be used to improve the
efficiency of administrative processes in healthcare businesses.
For example, machine learning algorithms can be used to analyze
patient data and identify patterns that can help to optimize
scheduling and resource allocation. Similarly, natural language
processing can be used to automate the processing of medical
records and other administrative documents, freeing up healthcare
professionals to focus on patient care. One of the most exciting
areas for intelligent technologies in healthcare is in the
development of personalized medicine. Personalized medicine uses
data analytics and other advanced technologies to identify the
unique characteristics of individual patients, and to tailor
treatment plans to their specific needs. For example, genetic data
can be used to identify patients who are at high risk of
developing certain diseases, and to provide personalized
interventions to prevent or treat those conditions. However, there
are also some challenges and concerns associated with the use of
intelligent technologies in healthcare. One of the biggest
concerns is around data privacy and security. Healthcare
businesses need to ensure that patient data is kept secure and
confidential, and that it is only used for legitimate purposes.
They also need to ensure that their employees are trained to use
intelligent technologies safely and ethically, and that they
understand the potential risks and limitations of these
technologies. In a general context, intelligent technologies have
the potential to transform the healthcare industry, offering a
range of benefits from improved patient outcomes to streamlined
administrative processes. However, healthcare businesses need to
be aware of the challenges and concerns associated with the use of
these technologies, and to take steps to ensure that they are used
safely and ethically. By doing so, they can unlock the full
potential of intelligent technologies to improve healthcare
outcomes for patients around the world.
Sections of interest include but are /_not limited_/ to:
/Section I — Introduction of AI and healthcare/
/Section II — Architectures and intelligent systems for AI and
healthcare convergence/
/Section III— IoT with Machine Learning and Artificial System
technologies/
/Section IV— AI and 6G mobile systems/
/Section V— AI enabled healthcare systems/
/Section VI— Performance Evaluation of Deep Learning and
IoT-related mechanisms/
/We strongly welcome _other topic suggestions_//./
_Schedule & Deadlines_
·*_31^st July 2023_*
Full chapter submission via e-mail:
gmastorakis@hmu.gr
<mailto:gmastorakis@hmu.gr>
·*_30^th September 2023_*
Review comments
·*_31^st October 2023_*
Submission of the revised version
·*_30^th November 2023 _*
Final acceptance notification
·*_31^st December 2023_**__*
Final manuscript
_Manuscript Preparation_
* Please follow the manuscript formatting guidelines below and
submit
the original version (in */Microsoft word/*) and or */LaTex/*
format
as per the guidelines
(URL:
https://www.springer.com/us/authors-editors/book-authors-editors/your-publication-journey/manuscript-preparation).
* Each final manuscript should be about 25-35 pages long
(formatted).
Depending on the number of submissions, longer manuscripts will
also
be accepted.
* Submit your chapter(s) via e-mail:
gmastorakis@hmu.gr
<mailto:gmastorakis@hmu.gr>
_______________________________________________
AISWorld mailing list
AISWorld@lists.aisnet.org