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Next Generation eHealth. Applied Data Science, Machine Learning and Extreme Computational Intelligence. Next Generation Technology Driven Personalized Medicine And Smart Healthcare

  • Book

  • October 2024
  • Elsevier Science and Technology
  • ID: 5917481
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. 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.

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.

Table of Contents

Dedication
Preface
Acknowledgements
Editorial Advisory Board
Related Titles
About the Author

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8. The Digital Healthcare Ecosystem in United Arab Emirates
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9. Linked Open Research Information on Semantic Web: Challenges & Opportunities for RIM Users
Otmane Azeroual
10. A Multi-objective Optimal Scheduling Patient Appointments Algorithm for Smart Healthcare
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11. An M-health application to collect and analyze gestational diabetes data
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Meena Gupta
13. Exploring Brain Tumors with ResNet 50 Transfer Learning: A Case of Air Pollution
Prisilla Jayanthi G, Iyyanki Krishna, Utku K�SE
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15. The Economic Feasibility of Digital Health and Telerehabilitation
Meena Gupta
16. Robust Artificial Intelligence and Machine Learning for Diseases Diagnosis
Cornelio Y��ez-M�rquez
17. The Data Strategy in the Madinah Health Cluster: Best Practices and Lessons Learnt from the application of Analytics Maturity Assessment
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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
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Authors

Miltiadis Lytras Research Professor, Deree College, The American College of Greece, Greece. 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. Abdulrahman Housawi Saudi Commission for Health Specialties, Saudi Arabia. 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 Saudi Commission for the Health Specialties, Riyadh, Saudi Arabia.

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.

Naif Radi Aljohani Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia. Naif Radi Aljohani works in the Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah in Saudi Arabia.