Artificial Intelligence in Digestive Endoscopy Training-The Past, Present, and Future.

Area of Science:

• Gastroenterology
• Medical Education
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is transforming gastrointestinal endoscopy.
• The role of AI in endoscopy training is currently underexplored.
• This review examines the evidence for AI in endoscopy training.

Purpose of the Study:

• To summarize current evidence on AI-assisted endoscopy training.
• To identify potential drawbacks and challenges of AI in training.
• To propose future directions for AI in endoscopy education.

Main Methods:

• A systematic MEDLINE search was conducted for AI and endoscopy training literature up to January 2025.
• Studies were screened for relevance, excluding reviews, letters, and those lacking a training focus.
• 27 articles were included after screening 1443 records.

Main Results:

• AI shows potential in improving endoscopy training across various types (luminal, hepatobiliary, capsule, therapeutic).
• Current AI applications are task-based, focusing on quality metrics, lesion detection, and landmark recognition.
• Future AI should offer comprehensive training and personalized feedback for endoscopists of all experience levels.

Conclusions:

• AI can enhance skill acquisition and procedural quality in endoscopy training.
• Significant gaps exist in current AI applications for endoscopy education.
• Further research is crucial for the widespread integration of AI in endoscopy training.