Buch, Englisch, 229 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 571 g
In honour of Professor Dr. George A. Tsihrintzis for his Invaluable Contributions
Buch, Englisch, 229 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 571 g
Reihe: Intelligent Systems Reference Library
ISBN: 978-3-031-98148-7
Verlag: Springer
This book brings together cutting-edge research and innovative applications of artificial intelligence, machine learning, wearable technologies and decision support systems in modern healthcare. The chapters demonstrate how these artificial intelligence innovations are driving next-generation healthcare solutions. The chapters present diverse clinical applications through advanced artificial intelligence approaches in diagnostics, treatment, rehabilitation and healthcare management, with a strong emphasis on patient-centred solutions. This book is directed to students, professors, researchers, practitioners in the field of healthcare, engineering, computer science and related areas.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
Weitere Infos & Material
Self-supervised and disease management system for diabetic retinopathy detection.- GAN-enhanced Abdominal MR-CT Image Fusion in Transform Domain.- U-Net with Attention for the Automatic Segmentation of the Major Temporal Arcade in Retinal Fundus Images.- Harnessing Few-Shot Learning Segmentation for Histopathology: A Comprehensive Practical Study.- Healthcare Applications of Object Detection for Tumor Detection Across Diverse Medical Imaging.- Automatic Multilabel Classification of Coronary Stenosis using Lightweight Deep
Learning Techniques.
