Exploring the influence of endoscopist characteristics and artificial intelligence on adenoma detection in colonoscopy.

ABSTRACT:

Background

Adenoma detection rate (ADR) is a key indicator of colonoscopy quality, but operator variability persists. Female clinicians may perform differently in other medical contexts, and artificial intelligence (AI) has been proposed to enhance detection. This study evaluated the impact of endoscopist characteristics and AI assistance on ADR in a real-world cohort.

Methods

This retrospective cohort study analyzed colonoscopy data from 17,604 patients in a single center in China between January 2021 and August 2022. Endoscopist characteristics were determined via survey, and AI-assisted procedures were identified based on implementation dates. The primary outcome was ADR; secondary outcomes included polyp detection rate (PDR), lesion size and location, and detection rates

SUBMITTER: Zhang C 

PROVIDER: S-EPMC12833059 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature