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Artificial Intelligence in Medical Robotics

  • Book

  • July 2024
  • Elsevier Science and Technology
  • ID: 5927240
Artificial Intelligence in Medical Robotics introduces novel ideas in medical robotics, focusing on applications of robots in surgery, nano-robotics, soft robots, and AI-enabled robots in the healthcare industry. This book also explores ethics and bias in the automation of healthcare, detailing the advance of AI for healthcare automation, robotic reinforcement learning, human-centered navigation, robotics and visualization for ophthalmic surgery, automation in eye surgery, human-machine perception and interaction in surgery, and the most recent advances and challenges in assistive and surgical robots in healthcare. This book will be a great source of information for researchers and academics in artificial intelligence, robotics, automation in healthcare, and autonomy in systems.

Table of Contents

1. Automation in Surgical Robotic
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

Authors

Mohamed Tounsi Associate Professor and Research Scientist, College of Computer & Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia. Mohamed Tounsi is an associate professor at Prince Sultan University, in Saudi Arabia. He is the founder of MEGDAM Data mining center in 2010, and was for several years chairman of the computer science department at PSU. His current research interests include designing algorithms, meta-heuristics, local search techniques, machine learning algorithms, and optimization in WSNs. He is very active in research and was granted a USTPO patent in the area of IoTs. He serves as a reviewer for a wide variety of journals, and is a senior member of the Automated Systems & Soft Computing Lab (ASSCL) at his university. Dr. Tounsi has expertise in meta-heuristics and optimization, IoT and robots controls, artificial intelligence, machine learning, and local search techniques. He has authored/co-authored several research papers in prestigious peer-reviewed journals, book chapters, and conference proceedings, and has participated in 30 European international, national and regional R&D projects. He is author of 30 JCR articles, 17 book chapters, three books, more than 200 papers presented at national and international congresses, four patents, four utility models and one industrial design.