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

>> *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@hmu.gr 
>> <mailto:gmastorakis@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@hmu.gr
>>     <mailto:gmastorakis@hmu.gr>
>>