Related Experiment Video
Updated: Jul 4, 2026

Structured Approach to Colonoscopy Technique Optimization: A Single-Center Experience with Novice Endoscopists
Published on: July 11, 2025
Training future endoscopists: gastroenterology fellows' perspectives and hands-on exposure to artificial intelligence
Tessa Herman1, Jason A Dominitz2,3, Tonya Kaltenbach4,5
1Department of Gastroenterology, Hepatology, and Nutrition, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Background And Aims:
Artificial intelligence (AI)-assisted colonoscopy for polyp detection is designed to improve colonoscopy quality. Although surveys have assessed staff gastroenterologists' attitudes toward AI, less is known about the views of gastroenterology (GE) fellows regarding AI during training.
Methods:
We conducted a nationwide survey of GE fellows from August 2024 to November 2024 to assess (1) exposure to and experience with AI in fellowship, (2) perceptions of AI's impact on colonoscopy quality, and (3) attitudes toward implementing AI into training. The survey included Likert scale questions with branching logic to tailor questions based on AI availability at the fellows' institutions.
Results:
A total of 126 fellows started the survey, and 88 (69.8%) completed it. AI was available at least at 1 training site for 69.3% of respondents. In addition, 81.8% of fellows believed AI should be available during fellowship. Many fellows (43.2%) thought AI should be incorporated in the second year of training. Most fellows (60.7%) believed early exposure to AI-enhanced polyp detection skills. However, 52.5% felt neutral that AI made them better endoscopists overall. Despite this, 62.5% preferred to pursue a job with AI if they had trained with it.
Conclusions:
Our nationwide survey found that GE fellows are generally supportive of integrating AI into their training, with most advocating for its incorporation in the second year. These results should be considered by fellowship program leadership and GE practices recruiting fellows trained with AI. Further studies are required to assess the impact of training GE fellows with AI on their polyp detection competency.
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