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

Status

Active, not recruiting

Phases

Study type

Interventional

Source

ClinicalTrials.gov

Registry ID

NCT06617468

Enrollment

120

Registered

2024-09-27

Start date

2024-09-20

Completion date

2024-12-31

Last updated

2024-10-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Colon Polyp

Keywords

colon polyp, optical diagnosis, computer-aided diagnosis

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.

Interventions

DIAGNOSTIC_TESTcomputer-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_TESTcomputer-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.

Study design

Allocation

RANDOMIZED

Intervention model

PARALLEL

Primary purpose

DIAGNOSTIC

Masking

NONE

Eligibility

Sex/Gender

ALL

Healthy volunteers

Inclusion criteria

* Endoscopists with colonoscopy experience

Exclusion criteria

* Who can not perform colonoscopy

Design outcomes

Primary

Measure	Time frame	Description
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

Measure	Time frame	Description
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.

Countries

South Korea

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026