Evaluation of an artificial intelligence system for polyp detection (CADe)
We aim to evaluate the artificial intelligence system ENDOMIND that supports endoscopist in detection of polyps during surveillance endoscopy for colorectal cancer. 1070 patients out of 6 gastroenterologic practice are randomized 1:1 for conventional surveillance colonoscopy vs. surveillance with AI support. Primary endpoint is Adenoma detection rate.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
1,149
CADe system for Polyp detection
Universitätsklinikum Würzburg
Würzburg, Bavaria, Germany
adenoma detection rate
proportion of individuals undergoing a complete screening colonoscopy who have one or more adenomas
Time frame: 4 months
polyp detection rate
Exmainations with minimum one polyp detected.
Time frame: 4 months
withdrawal time
Time of withdrawal.
Time frame: 4 months
resection time
Time spent on polyp resections.
Time frame: 4 months
Boston Bowl Preparation Score
minimum 0, Maximum 9; should be higher than 5 for appropriate surveillance
Time frame: 4 months
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