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>
>