Colonic Adenoma, Colon Polyp
Conditions
Keywords
Colonoscopy
Brief 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 identify the ability of physicians to distinguish artificial from real polyp images.
Interventions
OTHERLutetia
Lutetia is an AI-based training plattform
Sponsors
Wuerzburg University Hospital
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
BASIC_SCIENCE
Masking
NONE
Masking description
Participant does not know if pesented image is real or artificial
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Physicians with or without experience in colonoscopy
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Ability to detect artificial images as artificial | 6 months | The ability to recognise artificial images as being artificial, using an online questionnaire - binary question |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Ability to detect real images as real | 6 months | The ability to recognise real images as being real using an online questionnaire - binary question |
| Accuracy to correctly classify images | 6 months | Accuracy to correctly classify images using an online questionnaire |
Countries
Germany
Outcome results
None listed