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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
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.
Key Details
Gender
All
Age Range
Any - Any
Study Type
INTERVENTIONAL
Enrollment
120
Start Date
2024-09-20
Completion Date
2024-12-31
Last Updated
2024-10-04
Healthy Volunteers
No
Conditions
Interventions
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.
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.
Locations (1)
Healthcare System Gangnam Center, Seoul National University Hospital
Seoul, South Korea