*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_
·*_15^th September 2023 (deadline extended)_*
Full chapter submission via e-mail: [email protected]
<mailto:[email protected]>
·*_15^th October 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: [email protected]
<mailto:[email protected]>
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