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NCT04586556

Artificial Intelligence for Real-time Detection and Monitoring of Colorectal Polyps

Completed NA Last updated 25 November 2022
What this trial tests

NA trial testing Polyps detection by Artificial Intelligence in Adenomatous Polyps in 372 participants. Completed in 11 May 2022.

Timeline
18 December 2020
Primary endpoint
31 March 2022
11 May 2022

Quick facts

Lead sponsorCentre hospitalier de l'Université de Montréal (CHUM)
PhaseNA
StatusCompleted
Study typeINTERVENTIONAL
Allocationna
Designsingle group
Maskingnone
Primary purposediagnostic
Enrollment372
Start date18 December 2020
Primary completion31 March 2022
Estimated completion11 May 2022
Sites3 locations across France, Canada

Drugs / interventions tested

Conditions studied

Sponsor

Centre hospitalier de l'Université de Montréal (CHUM)

Who can join

Adults 45 to 80, any sex, with Adenomatous Polyps. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The investigators hypothesize that the clinical implementation of a deep learning AI system is an optimal tool to monitor, audit and improve the detection and classification of polyps and other anatomical landmarks during colonoscopy. The objectives of this study are to generate preliminary data to evaluate the effectiveness of AI-assisted colonoscopy on: a) the rate of detection of adenomas; b) the automatic detection of the anatomical landmarks (i.e., ileocecal valve and appendiceal orifice).

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

  1. Automated Detection of Anatomical Landmarks During Colonoscopy Using a Deep Learning Model.
    Taghiakbari M, Hamidi Ghalehjegh S, Jehanno E, Berthier T, et al · · 2023 · cited 4× · PMID 37538187 · DOI 10.1093/jcag/gwad017

Verify or expand the search:

Other recruiting trials for Adenomatous Polyps

Currently open trials in the same condition.

Other Centre hospitalier de l'Université de Montréal (CHUM) trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

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Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing