Call for Book Chapters for the Springer Book on Intelligent Technologies for Healthcare Business Applications

*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>