Actively Recruiting

Phase Not Applicable
Age: 18Years +
All Genders
Healthy Volunteers
NCT06550908

Training Physicians to Differentiate the Paris Classification Using Artificial Colon Polyp Images

Led by Wuerzburg University Hospital · Updated on 2025-08-12

70

Participants Needed

1

Research Sites

19 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

Training in endoscopy is essential for the early detection of precursors of colorectal cancer. Up to now, this training has been carried out with image collections of findings and in practice when working on patients. The investigators want to use artificial intelligence (AI) to better train doctors to recognise these precursors. By using generative AI, the investigators were able to create realistic images that comply with data protection regulations and whose content can be predefined. Parts of the image can also be regenerated so that it is possible to create different precancerous stages in the same place in the image. In this study the investigators want to train physicians using real images or artificial images in order to compare which version helps classify polyps better.

CONDITIONS

Official Title

Training Physicians to Differentiate the Paris Classification Using Artificial Colon Polyp Images

Who Can Participate

Age: 18Years +
All Genders
Healthy Volunteers

Eligibility Criteria

Eligible

You may qualify if you...

  • Physicians with or without experience in colonoscopy
Not Eligible

You will not qualify if you...

History of severe allergic reactions to study medication Currently pregnant or breastfeeding Recent participation in another clinical trial within the last 30 days Presence of uncontrolled medical conditions that could affect safety

AI-Screening

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Trial Site Locations

Total: 1 location

1

University hospital Würzburg

Würzburg, Germany

Actively Recruiting

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Research Team

A

Alexander Hann, MD

CONTACT

R

Ronja Weber

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

NONE

Allocation

RANDOMIZED

Model

PARALLEL

Primary Purpose

BASIC_SCIENCE

Number of Arms

2

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