Artificial Intelligence for Colorectal Surgeons-Part I: Foundations and Clinical and Educational Applications

Area of Science:

• Surgical Technology
• Medical Artificial Intelligence
• Colorectal Surgery Innovations

Background:

• Artificial intelligence (AI) is increasingly integrated into various aspects of colorectal surgery.
• This review provides a framework for understanding and implementing AI in surgical practice.
• The study focuses on Part I, covering fundamental AI concepts and clinical applications.

Purpose of the Study:

• To examine fundamental artificial intelligence (AI) concepts relevant to colorectal surgery.
• To review clinical applications of AI across the entire surgical continuum.
• To discuss educational considerations for colorectal surgeons regarding AI implementation.

Main Methods:

• A comprehensive literature review was conducted.
• The review focused on AI applications specifically within colorectal surgery.
• Evidence for clinical implementation and training approaches was evaluated.

Main Results:

• AI significantly improves adenoma detection rates in colonoscopy (40.4% to 54.8%).
• AI models predict surgical outcomes, outperforming traditional risk scores.
• AI applications span preoperative risk prediction, intraoperative guidance, and postoperative complication detection.

Conclusions:

• AI technologies are clinically validated for specific colorectal surgery applications.
• Successful AI integration requires understanding AI concepts, appropriate application, and structured training.
• Further research and implementation strategies are crucial for AI's transformative potential in surgery.