Endoscopy August 2022 PMID 34823258

Effect of an artificial intelligence-based quality improvement system on efficacy of a computer-aided detection system in colonoscopy: a four-group parallel study.

Liwen Yao, Lihui Zhang, Jun Liu, Wei Zhou, Chunping He, Jun Zhang, Lianlian Wu, Hongguang Wang, Youming Xu, Dexin Gong, Ming Xu, Xun Li, Yutong Bai, Rongrong Gong, Prateek Sharma

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Mentions

Peak: 5 in Aug 2022

across 3 sources since Jul 2022

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25,507

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Mentions per month

Jul 2022 – Aug 2022

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AI synopsis

What people are saying

The collective discussions show a moderate level of interest, as users mention key findings like improved adenoma detection and the potential synergy of combined AI systems. The tone is analytical, with some posts emphasizing how the research could influence future colonoscopy practices, demonstrating thoughtful engagement without overly hype or skepticism.

AgreementNeither agree nor disagree

The discussions reflect a neutral stance, with some users recognizing the potential benefits of integrating AI systems, but few showing strong opinions either way.

InterestModerate interest

Many posts express curiosity about the study, especially around AI's role in colonoscopy, but some show limited enthusiasm, focusing on sharing links or minimal commentary.

EngagementModerate engagement

Comments include references to the methodology and implications, such as notes on the 'synergistic benefit' of combining AI systems, indicating moderate engagement with the content's complexity.

ImpactModerate impact

Several posts highlight the clinical importance of improving detection rates with AI, suggesting awareness of meaningful enhancements in medical practices, although no post claims revolutionary change.

Abstract in brief

This study evaluated the impact of combining an artificial intelligence-based quality improvement system (CAQ) with a computer-aided detection system (CADe) during colonoscopy, finding that adding CAQ improved adenoma detection rates (ADR) compared to CADe alone, but not significantly different from CAQ alone.
The combination of CADe and CAQ (the COMBO group) resulted in higher ADR than CADe alone, suggesting a synergistic benefit, though it was not significantly better than CAQ alone, indicating that CAQ alone also significantly enhances detection efficacy.
Overall, the study highlights that the use of artificial intelligence systems, particularly CAQ, can improve colonoscopy outcomes, but combining systems may not always produce additive benefits beyond individual enhancements.]

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All mentions

AI-Based Quality System Improves Colonoscopy Detection Rates

This study evaluated the impact of combining an AI-based quality improvement system with a computer-aided detection system during colonoscopy, showing that adding the quality system improves adenoma detection rates…

endoscopythieme · Jul 27, 2022 26 views

Gastroenterology

@PracUpGastro · X

Effect of an Artificial Intelligence–Based Quality Improvement System on the Efficacy of a Computer-Aided Detection System in Colonoscopy https://t.co/9jz3bE4Kaj #gastroenterology

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Endoscopy Journal

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