Lytras / Housawi / Alsaywid Next Generation eHealth

Applied Data Science, Machine Learning and Extreme Computational Intelligence
1. Auflage 2024
ISBN: 978-0-443-13620-7
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 230 Seiten

Reihe: Next Generation Technology Driven Personalized Medicine And Smart Healthcare

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. - 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

Autoren/Hrsg.

Lytras, Miltiadis

Housawi, Abdulrahman

Alsaywid, Basim

Aljohani, Naif Radi