Reprint

Intelligent Medicine and Health Care

Edited by
March 2024
178 pages
  • ISBN978-3-7258-0569-3 (Hardback)
  • ISBN978-3-7258-0570-9 (PDF)

This book is a reprint of the Special Issue Intelligent Medicine and Health Care that was published in

Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

Intelligent medicine and health care are flourishing due to the integration of interdisciplinary factors, including artificial intelligence, electrophysiology, signal processing, medical imaging, complex theory, electronics, and clinics. We are entering an era in which multidimensional and big data play important roles in developing applications for medicine and health care. There are many state-of-the-art technologies and applications that address advanced data analysis and learning, embedded artificial intelligence, clinical decision support, ubiquitous patient monitoring, and rehabilitation. This Special Issue collected 10 recent studies on emerging interdisciplinary methods, techniques, and systems for intelligent medicine and health care.

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
mobile health; diabetes; architecture; mobile application; mobile operating system; mobile application; diabetes; architecture; trust components; testing; gait analysis; fall detection; wearable device; cross-platform; Institutional Review Board; image recognition; pill information retrieval; CNN; CBIR; machine learning; convolutional neural networks; AVQI; voice screening; Pareto optimization; voice disorders; dysphonia; voice quality; home health care routing and scheduling problem; resilience; information sharing; discrete event simulation; optimization; stretching; static stretching (SS); joint range of motion (ROM); muscle stiffness; joint–ligament–tendon–muscle unit; joint injuries—treatment and prophylaxis; parallelism; distributed systems; modified blockchain technology; personal health records; e-healthcare; human gait; criticality analysis; support vector machine; mental health; substance use disorder; machine learning; AutoML

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