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NCT Number: NCT06617468

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

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.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

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Key information

Conditions

Colon Polyp Colonic Polyps Intestinal Polyps Pathological Conditions, Anatomical Pathological Conditions, Signs and Symptoms Polyps

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Healthcare System Gangnam Center, Seoul National University Hospital

Seoul, 06236, South Korea

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Endoscopists with colonoscopy experience

Exclusion criteria

  • Who can not perform colonoscopy

Treatment and study plan

computer-aided diagnosis with explainable AI

Diagnostic Test

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

Diagnostic Test

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

Primary outcomes

  1. Accuracy of optical diagnosis

    Time frame: 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 outcomes

  1. acceptance of computer-aided diagnosis as a technology

    Time frame: 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.

Sponsors and collaborators

Lead sponsor

Seoul National University Hospital

Other

Registry information

Important dates

Study start
2024
Primary completion
2024
Study completion
2024
First posted
Sep 27, 2024
Registry last updated
Oct 4, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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