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Artificial Intelligence in Colonoscopy

NCT06786793 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 630

Last updated 2025-01-22

No results posted yet for this study

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.

Conditions

  • Quality Indicators, Health Care
  • Artificial Intelligence (AI)
  • Colonoscopy Diagnostic Techniques and Procedures

Interventions

DEVICE

Computer-aided detection (CADe)

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.

Sponsors & Collaborators

  • Jagiellonian University

    lead OTHER

Principal Investigators

  • Miroslaw Szura, Prof. · Jagiellonian University in Krakow

  • Zofia Orzeszko, MD · Jagiellonian University in Krakow

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
50 Years
Max Age
65 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-11-01
Primary Completion
2025-10-31
Completion
2025-12-31

Countries

  • Poland

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06786793 on ClinicalTrials.gov