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

Seoul National University

Status: Active, not recruiting

Conditions: Colon Polyp

Treatments: Diagnostic Test: computer-aided diagnosis with explainable AI; Diagnostic Test: computer-aided diagnosis with deep learning

Study type: Interventional

Funder types: Other

Identifiers

NCT06617468

2311-049-1482

Details and patient eligibility

About

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.

Enrollment: 120 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Endoscopists with colonoscopy experience

Exclusion criteria

• Who can not perform colonoscopy

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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120 participants in 2 patient groups

computer-aided diagnosis with explainable AI

Experimental group

Description:

Perform a same test to estimate the pathologic diagnosis on 200 NBI still images with computer-aided diagnosis with explainable AI

Treatment:

Diagnostic Test: computer-aided diagnosis with explainable AI

computer-aided diagnosis with deep learning

Active Comparator group

Description:

Perform a same test to estimate the pathologic diagnosis on 200 NBI still images with computer-aided diagnosis with deep learning

Treatment:

Diagnostic Test: computer-aided diagnosis with deep learning