Modern Technologies in Healthcare

AI, Computer Vision, Robotics
1. Auflage 2025
ISBN: 978-1-032-77233-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 347 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 800 g

Reihe: Analytics and AI for Healthcare

This book comprehensively explores the latest technological advancements in healthcare, with a particular focus on the application of cutting-edge technologies, such as artificial intelligence (AI), computer vision, and robotics. The focus extends across crucial domains, such as disease diagnosis and monitoring, medical imaging, and the facilitation of remote healthcare services.

The book provides a comprehensive overview of AI techniques for intelligent diagnoses, discussing how machine learning and deep learning models enhance accuracy and speed in medical imaging, diagnostics, and patient care. It also delves into the integration of AI with other disciplines, such as data science, computer vision, edge computing, robotics, and web development, to tackle complex medical challenges. Moreover, it highlights current trends and future prospects in surgery, rehabilitation, neuroscience, and automated healthcare systems, offering valuable insights into the future of technology-driven healthcare solutions. The chapters are authored by researchers and professionals from every region of the globe, including Africa, Asia, the Americas, Europe, and Oceania. This global contribution highlights the versatility and broad perspectives of the shared insights and conclusions presented in the book.

This book is an essential guide for healthcare professionals, researchers, and enthusiasts eager to understand and actively contribute to shaping the future of healthcare through the integration of AI and other disciplines.

Zielgruppe

Professional Practice & Development, Professional Reference, and Undergraduate Advanced

Autoren/Hrsg.

Komolafe, Blessing Funmi

Komolafe, Temitope Emmanuel

Wang, Nizhuan

Monkam, Patrice

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1. A deep learning method for identification of pneumonia from chest x-rays. 2. Recent development and applications of deep learning in medical imaging. 3. How to incorporate prior knowledge for effective fMRI data analysis: A comprehensive review and future direction. 4. AI applications in diagnostics and treatment. 5. eHealth platforms facilitate breast cancer: A systematic review. 6. Rehabilitation and assistive robotics for the elderly and physically challenged. 7. Surgical robots for minimally invasive surgery. 8. AI-aided tools for teaching and research in medical research. 9. Decoding neural signals: Invasive BMI review. 10. Real-time healthcare applications: Exploring the synergy of generative AI and edge computing/5G. 11. HealthSyncc: An AI-powered mobile application for health management. 12. Challenges and future trends in implementing AI in healthcare. 13. The future of AI in healthcare: Opportunities and challenges.

Über Autor(innen)

Temitope Emmanuel Komolafe is an Assistant Professor at the Collaborative Research Centre, Shanghai University of Medicine and Health Sciences. His research focuses on intelligent medicine, medical imaging processing, and precision rehabilitation robotics. He has published many research articles in peer-reviewed international journals.

Patrice Monkam is an Assistant Professor at Northeastern University, China. His research interests include image processing and analysis, medical imaging, and deep learning and its applications. He has authored over 20 research articles in leading peer-reviewed journals and at top-tier conferences.

Blessing Funmi Komolafe is a Lecturer at the College of International Education, Shanghai University of Medicine and Health Sciences. Her research focuses on pre-service physics teacher training, curriculum, pedagogy, medical education, and AI-based teaching. She has published extensively in international journals.

Nizhuan Wang is a Research Assistant Professor at the Hong Kong Polytechnic University, China. His research interests include brain-machine interface, neural computation, neuroimaging, neuroscience, and neurolinguistics. He has authored over 90 research articles in peer-reviewed top-tier journals and at conferences.