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

August 2022 Endoscopy

Synopsis of Social media discussions

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.

A
Agreement
 Neither 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.

I
Interest
 Moderate level of 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.

E
Engagement
 Moderate level of 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.

I
Impact
 Moderate level of 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.

Social Mentions

YouTube

1 Videos

Facebook

2 Posts

Twitter

5 Posts

Metrics

Video Views

26

Total Likes

1

Extended Reach

25,507

Social Features

8

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

AI-Based Quality System Improves Colonoscopy Detection Rates

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, highlighting AI's role in enhancing colonoscopy outcomes.

endoscopythieme

July 27, 2022

26 views

  • Gastroenterology
    @PracUpGastro (Twitter)

    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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    August 17, 2022

  • LibKey
    @libkey_io (Twitter)

    @endoscopyjrnl Help your colleagues avoid a paywall by accessing the article from their libraries: https://t.co/N8uzqdZAsI Simply add https://t.co/SXSePSX5De to the DOI URL when sharing articles on Twitter and everywhere else!
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    August 8, 2022

  • Endoscopy Journal
    @endoscopyjrnl (Twitter)

    Effect of an artificial intelligence-based quality improvement system on efficacy of a computer- aided detection system in colonoscopy: a fourgroup parallel study by Liwen Yao et al. Read more here: https://t.co/Ntk1cEqmmr https://t.co/p9yCadRbKE
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    August 8, 2022

    1

  • LibKey
    @libkey_io (Twitter)

    @endoscopyjrnl Help your colleagues avoid a paywall by accessing the article from their libraries: https://t.co/N8uzqdZAsI Simply add https://t.co/SXSePSX5De to the DOI URL when sharing articles on Twitter and everywhere else!
    view full post

    August 5, 2022

  • Endoscopy Journal
    @endoscopyjrnl (Twitter)

    #podcast Effect of an artificial intelligence-based quality improvement system on efficacy of a computer- aided detection system in colonoscopy: a fourgroup parallel study by Liwen Yao et al. Read more: https://t.co/Ntk1cEHXdZ Listen on YouTube: A https://t.co/uXUgahhcR1
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    August 5, 2022

Abstract Synopsis

  • 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.]