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Real-Time Artificial Intelligence Assissted Colonoscopy to Identify and Classify Polyps

NCT05718193 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 2868

Last updated 2023-04-11

No results posted yet for this study

Summary

To investigate the degree of the real-time detection and classification system for increasing the adenoma detection rate during colonoscopy.

Conditions

  • Artificial Intelligence
  • Colonoscopy
  • Quality Control

Interventions

DIAGNOSTIC_TEST

DeFrame

The DeFrame system is applicated during colonoscopy. The DeFrame system superimposes a rectangular box on the polyp lesion area in the colonoscopy field of view, notifying the endoscopists of the presence of the lesion.

DIAGNOSTIC_TEST

Classified DeFrame

The Classified DeFrame system is applicated during colonoscopy. The Classified DeFrame system superimposes a rectangular box on the polyp lesion area in the colonoscopy field of view, the color of the rectangle box will turn blue when the polyp is considered as an adenoma, notifying the endoscopists of the presence of the lesion.

DIAGNOSTIC_TEST

conventional colonoscopy

conventional colonoscopy

Sponsors & Collaborators

  • Loudi Central Hospital

    collaborator OTHER

  • Xiangya Hospital of Central South University

    lead OTHER

Principal Investigators

  • xiaowei liu, doctor · Xiangya Hospital of Central South University

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-06-01
Primary Completion
2023-02-28
Completion
2023-03-15

Countries

  • China

Study Locations

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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 NCT05718193 on ClinicalTrials.gov