Next Generation eHealth -

Next Generation eHealth

Applied Data Science, Machine Learning and Extreme Computational Intelligence
Buch | Softcover
230 Seiten
2024
Academic Press Inc (Verlag)
978-0-443-13619-1 (ISBN)
143,40 inkl. MwSt
Next 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. The title 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 the 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.

Miltiadis D. Lytras is an expert in advanced computer science and management, editor, lecturer, and research consultant, with extensive experience in academia and the business sector in Europe and Asia. Dr. Lytras is a Research Professor at Deree College - The American College of Greece and a Distinguished Scientist at the King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. Dr. Lytras is a world-class expert in the fields of cognitive computing, information systems, technology enabled innovation, social networks, computers in human behavior, and knowledge management. In his work, Dr. Lytras seeks to bring together and exploit synergies among scholars and experts committed to enhancing the quality of education for all. Dr. Abdulrahman Housawi is a nephrologist and specialist in multi-organ transplant surgery and Chairman of the Multi-organ Transplant Research Committee at King Fahd 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’s 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 (2016–present). Basim Alsaywid, Pediatric Urology Surgeon, graduated from King Abdulaziz University then completed Saudi Board of Urology in 2007. 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 a Master of Medicine degree from University of Sydney in Clinical Epidemiology with focus on biostatistics, then he completed a Master in Health Profession Education from King Saud Bin Abdulaziz University for Health Sciences, Saudi Arabia. Dr Alsaywid founded the research offices at 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. Dr. Naif Aljohani is a professor at the Faculty of Computing and Information Technology (FCIT) at King Abdul Aziz University, Jeddah, Saudi Arabia. He holds a PhD in Computer Science from the University of Southampton, UK. In 2009, he received a Master’s degree in Computer Networks from La Trobe University, Australia. His research interests are in the areas of His research interests are in the areas of learning and knowledge analytics, semantic web, web science, and big data analytics.

1. The Challenges for the Next Generation Digital Health: The disruptive character of Artificial Intelligence and Machine Learning
2. Data Governance in Health Clusters: Applying data strategy for accountable healthcare
3. Intelligent digital twins: Scenarios, promises and challenges in medicine and public health
4. Approximate Computing for Energy-Efficient Processing of Bio-signals in e-Health Care Systems
5. A smart Artificial intelligence and IoT based system for monitoring of COVID19 using chest X-ray images
6. Review of Data-Driven Generative AI Models for Knowledge Extraction from Scientific Literature in Healthcare
7. Machine Learning for dynamic composition of Health Education materials
8. The Digital Healthcare Ecosystem in United Arab Emirates
9. Linked Open Research Information on Semantic Web: Challenges & Opportunities for RIM Users
10. A Multi-objective Optimal Scheduling Patient Appointments Algorithm for Smart Healthcare
11. An M-health application to collect and analyze gestational diabetes data
12. E-Health and Cancer screening form scientific literature in healthcare
13. Exploring Brain Tumors with ResNet 50 Transfer Learning: A Case of Air Pollution
14. Wearable devices developed to support dementia detection, monitoring and intervention
15. The Economic Feasibility of Digital Health and Telerehabilitation
16. Robust Artificial Intelligence and Machine Learning for Diseases Diagnosis
17. The Data Strategy in the Madinah Health Cluster: Best Practices and Lessons Learnt from the application of Analytics Maturity Assessment
18. Integration of Digital Health Services for Education and Research Skills capacity building at the Saudi National Institute of Health
19. Enhancing Patient Welfare through Responsible and AI-Driven Healthcare Innovation: Progress Made in OECD Countries and the Case of Greece
20. Digital Health as a bold contribution to Sustainable and Social Inclusive Development

Erscheint lt. Verlag 1.10.2024
Reihe/Serie Next Generation Technology Driven Personalized Medicine And Smart Healthcare
Verlagsort San Diego
Sprache englisch
Maße 191 x 235 mm
Themenwelt Informatik Weitere Themen Bioinformatik
ISBN-10 0-443-13619-X / 044313619X
ISBN-13 978-0-443-13619-1 / 9780443136191
Zustand Neuware
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich