Ignite Creation Date:
2024-10-26 @ 3:37 PM
Last Modification Date:
2024-10-26 @ 3:37 PM
Study NCT ID:
NCT06550908
Status:
NOT_YET_RECRUITING
Last Update Posted:
None
First Post:
2024-08-08
Brief Title:
Training Physicians to Differentiate the Paris Classification Using Artificial Colon Polyp Images
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Training Physicians to Differentiate the Paris Classification Using Artificial Colon Polyp Images
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
LUTETIA2
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 We want to use artificial intelligence AI to better train doctors to recognise these precursors By using generative AI we 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 we want to train physicians using real images or artificial images in order to compare which version helps classify polyps better
In this study we want to train physicians using real images or artificial images in order to compare which version helps classify polyps better
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None