Artificial intelligence and robotic surgery: current perspective and future directions

Area of Science:

• Robotics
• Artificial Intelligence
• Surgical Technology

Background:

• Conventional surgical robots translate surgeon movements with tremor filtering.
• Next-generation robots align surgeon actions with pre-operative 3D plans.
• Advancements in AI, cloud computing, and big data fuel intelligent robot development.

Purpose of the Study:

• To outline the integration of artificial intelligence in robotic surgery.
• To identify challenges in implementing AI-driven surgical robots.

Main Methods:

• Review of advancements in AI, big data analytics, and deep learning.
• Highlighting key steps for handling and analyzing big data.
• Focus on building, defining, and deploying deep learning models for autonomous robots.

Main Results:

• Numerous companies are developing intelligent surgical robots.
• Deep learning is a key driver for autonomous robotic capabilities.
• Successful application of deep learning in various fields inspires surgical robotics.

Conclusions:

• Surgeon collaboration is essential for the next generation of intelligent robotic surgery.
• Despite progress, widespread adoption of autonomous robotics in operating rooms is still limited.
• Active surgeon involvement can accelerate the development and integration of advanced surgical robots.