Ignite Creation Date:
2024-05-06 @ 3:18 PM
Last Modification Date:
2024-10-26 @ 1:46 PM
Study NCT ID:
NCT04586556
Status:
COMPLETED
Last Update Posted:
2022-11-25
First Post:
2020-10-01
Brief Title:
Artificial Intelligence for Real-time Detection and Monitoring of Colorectal Polyps
Sponsor:
Centre hospitalier de lUniversité de Montréal CHUM
Organization:
Centre hospitalier de lUniversité de Montréal CHUM
Study Overview
Official Title:
Artificial Intelligence for Real-time Detection and Monitoring of Colorectal Polyps
Status:
COMPLETED
Status Verified Date:
2022-11
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
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 ie ileocecal valve and appendiceal orifice
Detailed Description:
In this trial the investigators aim to evaluate the followings
1 the accuracy of automatic detection of important anatomical landmarks ie ileocecal valve appendiceal orifice
2 the accuracy of automatic detection of polypsadenomas PDRADR
1 the accuracy of automatic detection of important anatomical landmarks ie ileocecal valve appendiceal orifice
2 the accuracy of automatic detection of polypsadenomas PDRADR
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None