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

Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Interventional
Study Phase: Not Applicable
SUMMARY

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.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Healthy Volunteers: t
View:

• Physicians with or without experience in colonoscopy

Locations
Other Locations
Germany
University hospital Würzburg
RECRUITING
Würzburg
Contact Information
Primary
Alexander Hann, MD
hann_a@ukw.de
0049931201
Backup
Ronja Weber
ronja.weber@stud-mail.uni-wuerzburg.de
0049931201
Time Frame
Start Date: 2025-04-15
Estimated Completion Date: 2025-08-31
Participants
Target number of participants: 70
Treatments
Active_comparator: Training with real images
Physicians train using the Paris classification with real colon polyp images
Experimental: Training with artificial images
Physicians train using the Paris classification with artificial colon polyp images
Sponsors
Leads: Wuerzburg University Hospital

This content was sourced from clinicaltrials.gov