Artificial Intelligence in Medical Robotics
Coordonnateur : Tounsi Mohamed
This book will be a great source of information for researchers and academics in artificial intelligence, robotics, automation in healthcare, and autonomy in systems.
2. Automation in Rehabilitation Robotic
3. Automation in Neuro-Robotic
4. Automation in Prosthetic
5. Autonomy in medical robotics
6. Supervised Robot Learning for Delivering Healthcare Services
7. Human-Machine Interfacing, Interaction, and Integration for Automation
8. Ethics in Automation of Healthcare delivery
9. Bias in Automation of Healthcare delivery
10. Advance AI for healthcare automation
11. Tools for Robotic Reinforcement Learning
12. Human-centered navigation
13. Robotics and Visualization for Ophthalmic Surgery
14. Task Automation in Eye Surgery
15. human-machine perception and interaction in Surgery
16. Advance in assistive robots in healthcare
17. Recent computational for soft robotic in healthcare
18. Challenges in surgical robotics
19. Machine learning for medical robotic domain
20. Supervised robotics autonomy
- Presents novel methodological approaches for applications of AI in medical and surgical robotics
- Investigates the challenges, human factors, and ethical concerns in the application of AI in healthcare automation
- Covers various advanced autonomous medical robots, with an emphasis on the role of humans in design and development
Date de parution : 11-2024
Ouvrage de 350 p.
15x22.8 cm
Thèmes d’Artificial Intelligence in Medical Robotics :
Mots-clés :
Medical robotics; autonomy in robotic; nano-robots in surgery; automation in prosthetic; supervised robot learning; artificial intelligence for surgical robots; automation of healthcare delivery; autonomous artificial intelligence; bias in automation of healthcare delivery; artificial intelligence for healthcare service robots; robotic reinforcement learning; human-centred navigation; robotics for ophthalmic surgery; automation in eye surgery; assistive autonomous robots in healthcare; soft robotic; machine learning for medical robots