Endoscopy April 2022 PMID 33951743

Endoscopists' diagnostic accuracy in detecting upper gastrointestinal neoplasia in the framework of artificial intelligence studies.

Leonardo Frazzoni, Julia Arribas, Giulio Antonelli, Diogo Libanio, Alanna Ebigbo, Fons van der Sommen, Albert Jeroen de Groof, Hiromu Fukuda, Masayasu Ohmori, Ryu Ishihara, Lianlian Wu, Honggang Yu, Yuichi Mori, Alessandro Repici, Jacques J G H M Bergman

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Mentions

Peak: 2 in May 2021

across 3 sources since May 2021

Extended reach

14,673

potential audience

Total likes

Video views

104

Mentions per month

May 2021 – Aug 2022

Where it's discussed

X / Twitter5 posts
Facebook2 posts
YouTube1 videos

AI synopsis

What people are saying

The collective discussions mainly revolve around sharing links to the publication and related media, with some posts mentioning AI and diagnostic accuracy in a neutral tone. Words like 'watch' and references to 'author commentary' contribute to a moderate level of interest and perceived importance, while the absence of critical or highly enthusiastic language indicates neutrality in agreement and engagement.

AgreementNeither agree nor disagree

The discussions show a neutral stance, as some posts reference the article without expressing strong support or disagreement.

InterestModerate interest

There is a moderate level of curiosity, evidenced by readers engaging with the publication through comments and video links, but without intense enthusiasm.

EngagementNeutral engagement

The interactions seem limited to sharing and discussing the publication, indicating a surface-level engagement rather than deep analysis.

ImpactModerate impact

The conversations suggest recognition of the study's relevance, especially regarding AI's role in diagnostics, but without widespread calls for immediate change.

Abstract in brief

This study evaluates how accurately endoscopists can detect upper gastrointestinal neoplasia (UGIN), with a focus on the role of artificial intelligence (AI) in improving diagnostic performance.
The analysis of seven studies involving 122 endoscopists shows that they have an overall sensitivity of 82% and specificity of 79% in detecting UGIN, with higher accuracy for gastric adenocarcinoma compared to other neoplasias.
Despite the use of AI validation, endoscopists still show suboptimal accuracy, highlighting the need for better training, infrastructure, and quality assurance programs to accurately diagnose upper GI cancers.]

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All mentions

AI's Role in Improving Endoscopists' Detection of Upper Gastrointestinal Neoplasia

Giulio Antonelli discusses endoscopists' diagnostic accuracy for upper gastrointestinal neoplasia, emphasizing the potential of AI validation studies to enhance detection accuracy and the need for improved training and…

endoscopythieme · Mar 29, 2022 104 views

Oncology & Machine Learning

@MlOncology · X

Correction: Endoscopists' diagnostic accuracy in detecting upper gastrointestinal neoplasia in the framework of artificial intelligence studies https://t.co/aYcbE4n9H5

Aug 2, 2022 · 213 followers View post →

Mario Dinis-Ribeiro

@mdinisribeiro · X

RT @endoscopyjrnl: #authorcommentary Giulio Antonelli on "Endoscopistsʼ diagnostic accuracy in detecting upper GI neoplasia in the framewor…

Apr 14, 2022 · 1 share · 393 followers View post →

Endoscopy Journal

@endoscopyjrnl · X

Apr 14, 2022 · 1 like · 1 share · 11,564 followers View post →

TechnoJeder A.I.

@TechnoJeder · X

RT @MlOncology: Endoscopist Diagnostic Accuracy in Detecting Upper-GI Neoplasia in the Framework of Artificial Intelligence Studies https:/…

May 6, 2021 · 1 share · 2,179 followers View post →