Ignite Creation Date:
2025-12-24 @ 5:47 PM
Ignite Modification Date:
2025-12-24 @ 5:47 PM
Study NCT ID:
NCT06617468
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2024-10-04
First Post:
2024-09-25
Is Possible Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Effect of the Computer Aided Diagnosis with Explainable Artificial Intelligence for Colon Polyp on Optical Diagnosis and Acceptance of Technology
Sponsor:
Seoul National University Hospital
Organization:
Study Overview
Official Title:
Effect of the Computer Aided Diagnosis with Explainable Artificial Intelligence for Colon Polyp on Optical Diagnosis and Acceptance of Technology
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2024-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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.
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:
None
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?: