附註:Includes bibliographical references and index.
Chapter 1. Quantum-based robotics in the high-tech healthcare industry: innovations and applications -- Chapter 2. Application of medical robotics in healthcare sector -- Chapter 3. Diagnosis of inflamed urinary bladder by creating a new classifier -- Chapter 4. Diabetes and pre-diabetes prediction by AI using tuned XGB classifier -- Chapter 5. Multi-modal MRI images analysis for improved herniated disc diagnosis using deep learning -- Chapter 6. Real-time sign language recognition -- Chapter 7. Energy efficiency and human comfort: AI and IoT integration in hospital HVAC systems -- Chapter 8. Brain interaction assessment using EEG source localization: sloreta -- Chapter 9. Detection of drowsiness in drivers using tensorflow framework -- Chapter 10. Challenges exist in translating brain signals into words using brain-computer interfaces (BCIs) -- Chapter 11. AI integrated with IoT system for continuous elderly fall detection using smartfallsentry system -- Chapter 12. Machine learning advancements in e-health: transforming digital healthcare -- Chapter 13. Hepatitis c prediction using feature selection by machine learning technique -- Chapter 14. Emerging MRI techniques in clinical practice of cerebrovascular diseases -- Chapter 15. A novel human embryo microscope image classification technique based on convnextlarge model -- Chapter 16. Identification of insecurity in COVID-19 using machine learning techniques -- Chapter 17. Precision medicine: insights from case studies and cutting-edge technologies -- Chapter 18. Wearable IoT devices in rehabilitation: enabling personalized precision medicine -- Chapter 19. Revolutionizing healthcare: the application of image processing techniques -- Chapter 20. The future of medical robotics and AI-assisted diagnostics -- Chapter 21. Cloud platform and data storage systems in the healthcare ecosystem -- Chapter 22. An innovative cloud computing for medical laboratory data storage and analytics -- Chapter 23. Security challenge
摘要:"While ultra-high field strength diagnosis technologies and artificial intelligence have propelled medicine imaging towards microstructure analysis and precise medicine, persistent challenges remain. These range from long scanning times to motion sensitivity and issues with imaging quality for certain types of tissue. Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry summarizes emerging techniques, outlines clinical applications, and confronts the challenges head-on, proposing avenues for further research. It explores emerging techniques such as human-like robotics, medical Internet of Things (IoT), low-cost CT scanners, portable MRI devices, and breakthroughs in diagnosistechnologies like zero echo time (ZTM) and compressed sensing volume interpolation breath-holding test sequences (CS-VIBE).This book provides an overview of the current state of medical imaging and clinical diagnosis applications, then expands into a roadmap for the future, envisioning the seamless integration of medical robotics and AI-assisted applications in the high-tech healthcare industry. As the influence of artificial intelligence continues to grow, the book serves asa clarion call for collaborative efforts, increased research, and unified strategies to navigate the challenges and harness the opportunities presented by the high-tech medical industry. This book is ideal for medical analysts, healthcarescientists, biotechnology analysts, scholars, researchers, academics, professionals, engineers, and students worldwide."--
