Abstract
Background & aims: One-fourth of colorectal neoplasias are missed during screening colonoscopies; these can develop into colorectal cancer (CRC). Several deep learning based real-time computer-aided detection (CADe) systems proved their efficacy in improving the performance of expert endoscopists in neoplasia detection. We performed a multicenter, randomized trial to assess the efficacy of a CADe system in detection of colorectal neoplasias in a non-expert setting to challenge the CADe impact in a real-life scenario.
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