Artificial Intelligence in Colonoscopy
Artificial Intelligence in Endoscopic Diagnosis of Colorectal Polyps: A Prospective Randomized Study.
Jagiellonian University
630 participants
Nov 1, 2024
INTERVENTIONAL
Conditions
Summary
Colorectal cancer is the second most common malignancy in the countries of the European Union. Colonoscopy is the primary method for detecting and preventing the development of colorectal cancer is endoscopic examination. This study aims to evaluate the impact of artificial intelligence on the detection rate of polyps and early stages of colorectal cancer.
Eligibility
Inclusion Criteria3
- Consent to participate in the study,
- Age between 50 and 65 years,
- Scheduled outpatient colonoscopy.
Exclusion Criteria8
- Previous colonoscopy,
- History of colorectal surgery,
- Ongoing biological therapy for any indication,
- Primary sclerosing cholangitis,
- Familial polyposis syndrome,
- Chronic diarrhea,
- Ulcerative colitis,
- Crohn's disease.
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Interventions
Endo-Aid CADe system is an AI-assisted computer-aided lesion detection application on ENDO-AID hardware. It uses a complex algorithm created via a neural network developed and taught by Olympus. With this new app, the sophisticated machine learning system can alert the endoscopist in real-time when a suspicious lesion appears on the screen. The image from the vision processor is transferred to the CADe device. The computer application recognizes the shape of the polyps and marks their place on the monitor screen.
Locations(2)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT06786793