Effect of the Computer Aided Diagnosis with Explainable Artificial Intelligence for Colon Polyp on Optical Diagnosis and Acceptance of Technology

October 2, 2024 updated by: Su Jin Chung, Seoul National University Hospital

The goal of this clinical trial is to learn if computer-aided diagnosis with deep learning and computer-aided diagnosis with explainable AI work to optical diagnosis performance and acceptance of technology in endoscopists. The main questions it aims to answer are:

Do computer-aided diagnosis with deep learning and computer-aided diagnosis with explainable AI improve optical diagnosis performance in endoscopists?

Does experience using deep learning-based computer-assisted diagnosis and explainable AI-based computer-assisted diagnosis improve endoscopists' acceptance of computer-aided diagnosis as a technology?

Participants will:

Conduct a survey on acceptance and use of technology about computer-aided diagnosis.

Perform a test to estimate the pathologic diagnosis on 200 NBI still images without the aid of computer-aided diagnosis.

More than 1 month later, perform a same test to estimate the pathologic diagnosis on 200 NBI still images with computer-aided diagnosis with deep learning or explainable AI.

Conduct a survey on acceptance and use of technology about computer-aided diagnosis.

Study Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

120

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Korea, Republic of
      • Seoul, Korea, Republic of, 06236
        • Healthcare System Gangnam Center, Seoul National University Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Endoscopists with colonoscopy experience

Exclusion Criteria:

  • Who can not perform colonoscopy

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: computer-aided diagnosis with explainable AI
Perform a same test to estimate the pathologic diagnosis on 200 NBI still images with computer-aided diagnosis with explainable AI
Diagnostic test: computer-aided diagnosis with explainable AI
Perform a same test to estimate the pathologic diagnosis on 200 NBI still images with computer-aided diagnosis with explainable AI.
Active Comparator: computer-aided diagnosis with deep learning
Perform a same test to estimate the pathologic diagnosis on 200 NBI still images with computer-aided diagnosis with deep learning
Diagnostic test: computer-aided diagnosis with deep learning
Perform a same test to estimate the pathologic diagnosis on 200 NBI still images with computer-aided diagnosis with deep Iearning.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy of optical diagnosis
Time Frame: From baseline test to the follow up test (more than 1 month later from baseline test)
The proportion of cases in which pathological results are consistent with endoscopic estimation of adenoma and hyperplastic polyp
From baseline test to the follow up test (more than 1 month later from baseline test)

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
acceptance of computer-aided diagnosis as a technology
Time Frame: From baseline test to the follow up test (more than 1 month later from baseline test)
Survey on acceptance and use of technology about computer-aided diagnosis.
From baseline test to the follow up test (more than 1 month later from baseline test)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Seoul National University Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 20, 2024

Primary Completion (Estimated)

December 31, 2024

Study Completion (Estimated)

December 31, 2024

Study Registration Dates

First Submitted

September 25, 2024

First Submitted That Met QC Criteria

September 25, 2024

First Posted (Actual)

September 27, 2024

Study Record Updates

Last Update Posted (Actual)

October 4, 2024

Last Update Submitted That Met QC Criteria

October 2, 2024

Last Verified

September 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2311-049-1482

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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