Artificial Intelligence for Standardisation and Quality Assessment in Robotic Colorectal Surgery: A Narrative Review

Area of Science:

• Robotic Surgery
• Artificial Intelligence
• Surgical Workflow Analysis

Background:

• Robotic colorectal surgery is widely used but lacks standardized intraoperative practices.
• Significant variability exists in surgical setup, workflow, and technical performance.

Purpose of the Study:

• To review artificial intelligence (AI) applications in robotic colorectal surgery.
• Focus on AI's role in workflow analysis, technical performance assessment, and intraoperative assistance.

Main Methods:

• Conducted a narrative review of studies from PubMed and Medline.
• Identified AI applications in robotic colorectal and other surgical specialties.

Main Results:

• AI analysis of surgical video and robotic data can characterize workflow, technical execution, and safety events.
• Supports process-based quality assessment in surgery.
• Limitations include generalizability, interpretability, and validation challenges.

Conclusions:

• AI is unlikely to automate standardization in robotic colorectal surgery.
• AI's primary value is in observing and measuring surgical processes.
• Enables mediated standardization while preserving surgeon judgment and responsibility.