[Om-announce] Call for Book Chapters for the Springer Book on Intelligent Technologies for Healthcare Business Applications - Deadline Extended
George Mastorakis
mastorakis at gmail.com
Fri Sep 1 11:04:55 CEST 2023
> *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: gmastorakis at hmu.gr
> <mailto:gmastorakis at hmu.gr>
>
> ·*_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: gmastorakis at hmu.gr
> <mailto:gmastorakis at hmu.gr>
>
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