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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
70
Training platform Lutetia offers training the Paris classification using real images of colon polyps.
Training platform Lutetia offers training the Paris classification using artificial images of colon polyps.
University hospital Würzburg
Würzburg, Germany
RECRUITINGAccuracy for Paris classification
Ability to correctly classify colonic polyps using the Paris classification
Time frame: 9 months
Range of misclassifications for Paris classification
Number of misclassification categorizes (eg 1-4)
Time frame: 9 months
Influence of endoscopy experience on accuracy for correct Paris classification
Influence of endoscopy experience measured in number of perfomed colonoscopies on accuracy for correct Paris classification
Time frame: 9 months
Influence of time to complete course on accuracy for correct Paris classification
Influence of time to complete course measured in days on accuracy for correct Paris classification
Time frame: 9 months
Influence regular usage of Paris classification on accuracy for correct Paris classification
Influence regular usage of Paris classification (yes/no) on accuracy for correct Paris classification
Time frame: 9 months
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