Ignite Creation Date:
2024-10-26 @ 3:41 PM
Last Modification Date:
2024-10-26 @ 3:41 PM
Study NCT ID:
NCT06617468
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
None
First Post:
2024-09-25
Brief Title:
Effect of the Computer Aided Diagnosis with Explainable Artificial Intelligence for Colon Polyp on Optical Diagnosis and Acceptance of Technology
Sponsor:
None
Organization:
None
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:
No
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:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None