Next Generation eHealth
Applied Data Science, Machine Learning and Extreme Computational Intelligence
- 1st Edition - September 30, 2024
- Imprint: Academic Press
- Editors: Miltiadis Lytras, Abdulrahman Housawi, Basim Alsaywid, Naif Radi Aljohani
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 3 6 1 9 - 1
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 3 6 2 0 - 7
Next Generation eHealth: Applied Data Science, Machine Learning and Extreme Computational Intelligence discusses the emergence, the impact, and the potential of sophis… Read more
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Request a sales quoteNext Generation eHealth: Applied Data Science, Machine Learning and Extreme Computational Intelligence discusses the emergence, the impact, and the potential of sophisticated computational capabilities in healthcare. This book provides useful therapeutic targets to improve diagnosis, therapies, and prognosis of diseases, as well as helping with the establishment of better and more efficient next-generation medicine and medical systems. Machine learning as a field greatly contributes to next-generation medical research with the goal of improving medicine practices and medical Systems. As a contributing factor to better health outcomes, this book highlights the need for advanced training of professionals from various health areas, clinicians, educators, and social professionals who deal with patients. Content illustrates current issues and future promises as they pertain to all stakeholders, including informaticians, professionals in diagnostics, key industry experts in biotech, pharma, administrators, clinicians, patients, educators, students, health professionals, social scientists and legislators, health providers, advocacy groups, and more. With a focus on machine learning, deep learning, and neural networks, this volume communicates in an integrated, fresh, and novel way the impact of data science and computational intelligence to diverse audiences.
- Allows medical scientists, computer science experts, researchers, and health professionals to better educate themselves on machine Learning practices and applications and to benefit from the improvement of their knowledge skills
- Provides various tested and current techniques of health literacy as a determinant of health and well-being
- Provides insight into international research successfully implemented in patient care and education through the proper training of health professionals
- Offers detailed guidance for diverse communities on their need to get timely, trusted, and integrated knowledge for the adoption of ML in healthcare processes and decisions. professionals involved with healthcare to leverage productive partnerships with technology developers
Researchers and graduate students in medical informatics, healthcare professionals, Researchers and graduate students in life sciences
- Title of Book
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- About the editors
- Other titles by this editor
- Acknowledgments
- Introduction
- Next generation eHealth: Applied data science, machine learning and extreme computational intelligence
- Section 1: Challenges, governance economic feasibility of the AI in healthcare, and its impact on enhanced patients' outcomes
- Section 2: AI in healthcare: Indicative Applications, Services, Models and Implementations
- Section 3: AI as a catalyst for Health Market, Health Education, Health Sustainability, and Social Inclusive Economic Development
- Chapter 1. The challenges for the next generation digital health
- 1 Introduction
- 2 Artificial Intelligence as a value-based ecosystem for digital health
- 2.1 The unique value proposition of Artificial Intelligence
- 2.2 A proposed value-based ecosystem for AI-enabled Digital Health
- 3 Disruptive scenarios and use case for AI-Enabled Next Generation Digital Health Services and Solutions
- 3.1 Disruptive NextGen AI-enabled digital health use cases
- 3.2 Use case scenarios for the integration of AI in diverse eHealth settings
- 4 Discussing the early-adoption era of next generation digital health
- 5 Conclusions
- Index
- Edition: 1
- Published: September 30, 2024
- Imprint: Academic Press
- No. of pages: 338
- Language: English
- Paperback ISBN: 9780443136191
- eBook ISBN: 9780443136207
ML
Miltiadis Lytras
Miltiadis D. Lytras is an expert in advanced computer science and management, with extensive experience in academia and the business sector in Europe and Asia. He is a Research Professor at Deree College—The American College of Greece and a Distinguished Scientist at King Abdulaziz University, Saudi Arabia. Dr. Lytras specializes in cognitive computing, information systems, technology-enabled innovation, social networks, and knowledge management. He has coedited over 110 high-impact special issues in ISI/Scopus-indexed journals and authored more than 80 books with international publishers. Additionally, he has published over 120 high-impact papers in top-tier journals such as IEEE Transactions on Knowledge and Data Engineering and the Journal of Business Research. With 25 years of experience in Research and Development projects, Dr. Lytras has been involved in more than 70 R&D projects globally. He holds senior editorial positions in prestigious journals and is the Founding Editor and Editor in Chief of the International Journal on Semantic Web and Information Systems.
Affiliations and expertise
Effat University, Computer Science Department, College of Engineering, Jeddah, Saudi ArabiaAH
Abdulrahman Housawi
Dr. Abdulrahman Housawi is a Nephrologist and Specialist in multiorgan transplant surgery and Chairman of the Multi-organ Transplant Research Committee at King Fahad Specialist Hospital, Dammam, KSA. He received his medical degree from the King Abdulaziz University in Jeddah, Saudi Arabia, his Master of Science degree with a focus on epidemiology and biostatistics from the University of Western Ontario, London, Canada, and a Master of Science in Health Administration from the University of Alabama, Birmingham. His research interests include the epidemiology of chronic kidney disease, developing research registries for CKD and solid organ transplants, the outcomes of living kidney donation and the long-term outcomes of kidney transplantation. From the PH-LEADER workshops, he hopes to further his knowledge of transplants and outside aspects of surgery and its effects on the donors and their families. Currently, he is responsible for the development and implementation of the Saudi Commission’s strategy, including its transformation to a data-driven organization (2016epresent).
Affiliations and expertise
Ministry of Health, Saudi ArabiaBA
Basim Alsaywid
Basim Alsaywid, Pediatric Urology Surgeon, graduated from King Abdulaziz University then completed Saudi Board of Urology in 2007. He obtained his Pediatric Urology Training Certificate from a fellowship at Westmead Children Hospital and then Sydney Children Hospital at Randwick, Sydney, Australia. During his fellowship training, he completed his Master of Medicine degree from the University of Sydney in Clinical Epidemiology with focus on biostatistics, and then he completed his Master’s in Health Profession Education from King Saud Bin Abdulaziz University for Health Sciences, Saudi Arabia. Dr. Alsaywid founded the research offices at the College of Medicine and College of Applied Health Sciences at King Saud Bin Abdulaziz University for Health Sciences in Jeddah. Also, he founded and chaired the Research and Development Department at Saudi Commission for Health Specialties in Riyadh. Currently, Dr. Alsaywid is the Director of Education and Research Skills at Saudi National Institute of Health, Riyadh, Saudi Arabia.
Affiliations and expertise
Saudi National Institute of Health, Education and Research Skills Directory, Riyadh, Saudi ArabiaNA
Naif Radi Aljohani
Dr. Naif Aljohani is a Professor at the Faculty of Computing and Information Technology (FCIT) in King Abdul Aziz University, Jeddah, Saudi Arabia. He holds a PhD in Computer Science from the University of Southampton, UK. In 2009, he received his master’s degree in Computer Networks from La Trobe University, Australia. His research interests are in the areas of learning and knowledge analytic, semantic web, web science, and big data analytics.
Affiliations and expertise
King Abdulaziz University, Jeddah, Saudi ArabiaRead Next Generation eHealth on ScienceDirect