TITLE New artificial intelligence system: first validation study versus experienced endoscopists for colorectal polyp detection
FIRST AUTHOR Cesare Hassan (Digestive Endoscopy, Nuovo Regina Margherita Hospital, Rome, Italy)
PUB DATE October 2019 (online), October 2020 (print)
Validate GI Genius™ Intelligent Endoscopy Module using a dataset of white light endoscopy videos.
Validate the artificial intelligence system using images from 2684 histologically confirmed polyps from 840 patients enrolled in a randomized controlled trial. Patients were randomized to either the validation or the training group.
Validation videos included 338 polyps from 105 patients. 49.7% were adenomas or sessile serrated adenomas (N=168).
Polyp video clips were created starting 5 seconds prior to the polyp visualization:
- True positive defined as a target polyp detected by the AI system.
- False negative defined as no target polyp detected.
Reaction time was compared between the AI and that of a panel of 5 expert endoscopists.
Overall sensitivity per lesion was 99.7% (337 true positive, 1 false negative):
- Nearly 100% sensitivity of AI-assisted colonoscopy regardless of shape, size, location, and histology of the lesion did not impact detection ability.
- False positives were ≤1%.
- AI-assisted colonoscopy had a faster reaction time than the average of the endoscopists detection in 82% of polyps (AI-assisted colonoscopy was 1.27 + 3.81 seconds faster).
The validation of the GI Genius™ Intelligent Endoscopy Module produced high sensitivity, minimal false positives, and was faster than expert endoscopists at detecting polyps in the majority of polyps in the dataset.
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