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

Not Applicable

Active, not recruiting

• Conditions: Colon Polyp

• Registration Number: NCT06617468
• Lead Sponsor: Seoul National University Hospital

Brief Summary

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.

Detailed Description

Not available

Study Timeline

• Status Verified: 2024-09
• Study Start: 2024-09-20
• Study First Submitted: 2024-09-25
• Study First Submitted QC: 2024-09-25
• Study First Posted: 2024-09-27
• Last Update Submitted: 2024-10-02
• Last Update Posted: 2024-10-04
• Primary Completion: 2024-12-31
• Study Completion: 2024-12-31

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 120

Inclusion Criteria

• Endoscopists with colonoscopy experience

Exclusion Criteria

• Who can not perform colonoscopy

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
Accuracy of optical diagnosis	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

Secondary Outcome Measures

Name	Time	Method
acceptance of computer-aided diagnosis as a technology	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.

Trial Locations

Locations (1)

Healthcare System Gangnam Center, Seoul National University Hospital; 🇰🇷 Seoul, Korea, Republic of