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Efficacy of Real-Time Computer Aided-Detected of Colonic Neoplasia in an Underserved Population, A Randomized Controlled Trial
This study assesses the sensitivity and added benefits of computer-aided detection compared to standard care (white-light) in detecting colon polyps in patients undergoing colonoscopy.
Failure in polyp detection leads to colon cancer after colonoscopy. Artificial intelligence systems allow real-time computer-aided detection of polyps with high-accuracy. This study will compare GI-Genius, a real-time CAD system to standard colonoscopy in terms of how many colonoscopies detect an adenoma.
Age
30 - 100 years
Sex
ALL
Healthy Volunteers
No
Riverside University Health System
Moreno Valley, California, United States
Start Date
September 1, 2022
Primary Completion Date
March 31, 2023
Completion Date
May 27, 2023
Last Updated
July 27, 2023
1,100
ACTUAL participants
Real-Time Computer Aided Detection
DEVICE
Stanford Colonoscopy
PROCEDURE
Lead Sponsor
Riverside University Health System Medical Center
NCT04704661
NCT06696768
Data Source & Attribution
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