An observational study in Focus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp Detection, sponsored by Johannes Gutenberg University Mainz. Status unknown at 1 site in Germany. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2020-09-07.
Sponsored by Johannes Gutenberg University Mainz · Observational
Linked color imaging (LCI) has shown its effectiveness in multiple randomized controlled trials for enhanced colorectal polyp detection. Most recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is increasingly recognized as a promising new technique enhancing colorectal polyp detection. Study aim was to evaluate a new developed deep-learning computer-aided detection (CAD) system in combination with LCI for colorectal polyp detection.
385 studies on the registry are indexed under Polyps; 59 are open to participants now.
This study's planned enrollment of 600 is above the median of 271 across 128 observational studies indexed under Polyps.
Browse Polyps studies →Johannes Gutenberg University Mainz is the lead sponsor of 153 studies on the registry; 20 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Patients ondergoing screeining or surveillance endoscopy
Exclusion Criteria:
Polyps within fully recorded endoscopy videos with LCI mode, covering the whole spectrum of adenomatous histology, are used to evaluate the efficacy of CAD with LCI for polyp detection.
Colorectal polyp detection rate in comparison to traditional detection rate
Time frame: 2019-2020
Plan to share: Undecided
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This study is status unknown, as verified in Sep 2020. You cannot join it, but the record below documents what was studied.
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Johannes Gutenberg University Mainz