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AI-Driven Healthcare Technologies and Interactive Systems for Medical Education

Jin Liu (Shanghai University of Engineering Science, China), Damin Ding (Shanghai University of Engineering Science, China), Haima Yang (University of Shanghai for Science and Technology, China), and Jingru Zhang (Jiangsu Ocean University, China)
Projected Release Date: July, 2026 | Copyright: © 2027 | Pages: 515

Publication Status: Coming Soon
ISBN13: 9798337392400
ISBN13 Softcover: 9798337392417
EISBN13: 9798337392424
DOI: 10.4018/979-8-3373-9240-0

Description:

Artificial intelligence (AI) has become a transformative force in modern healthcare, reshaping the ways medical data are analyzed, clinical decisions are supported, and healthcare professionals are trained. Advances in machine learning, medical imaging, robotics, and intelligent systems have enabled new approaches to diagnosis, treatment, and healthcare service delivery. At the same time, the increasing complexity of healthcare technologies has highlighted the importance of interactive systems, human-centered design, and effective educational frameworks to ensure their safe, ethical, and meaningful adoption.

AI-Driven Healthcare Technologies and Interactive Systems for Medical Education explores the interdisciplinary landscape of AI-driven healthcare technologies, with a particular focus on interactive systems, and their impact on medical education. By bringing together perspectives from AI, biomedical engineering, human–computer interaction, design, and educational technology, the book examines both the technical foundations and the applied dimensions of intelligent healthcare systems. Covering topics such as clinical training, immersive systems, and wearable sensor systems, this book is an excellent academic resource for graduate and doctoral students, healthcare professionals, engineers, instructional designers, and more.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence (AI)
  • Clinical Training
  • Deep Learning
  • Diagnostics
  • Healthcare Technologies
  • Human-Centered Design
  • Immersive Technologies
  • Interactive Systems
  • Machine Learning
  • Medical and Health Data
  • Medical Education
  • Medical Image Processing
  • Policy Implications
  • Public Health Opportunities
  • Wearable Sensor Systems

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