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Gastroenterology and Artificial Intelligence: 2nd ...
RealTeam Detection and Characterization of Colon P ...
RealTeam Detection and Characterization of Colon Polyps with Videos_ Mori
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In this document, the speaker discusses the implementation of artificial intelligence (AI) in colonoscopy procedures. They highlight two key roles of AI in colonoscopy: automated polyp detection (CADe) and automated polyp characterization (CADx). The speaker references several studies that have shown promising results in improving adenoma detection rates (ADR) with the use of AI. They also mention the importance of regulatory approval and reimbursement for AI technologies in colonoscopy.<br /><br />The speaker discusses the availability of publicly accessible and fully annotated colonoscopy-video databases, which provide a valuable resource for training and testing AI algorithms. They emphasize the importance of quality-assured labeling and regulatory compatibility in ensuring the reliability and approval of AI technologies.<br /><br />The speaker also highlights the cost-effectiveness of AI in colonoscopy. They mention that the use of AI can help reduce unnecessary polypectomies and save significant costs. The speaker references a micro simulation study that suggests a reduction in colorectal cancer incidence and mortality with the use of AI.<br /><br />Finally, the speaker mentions that there are multiple AI tools for colonoscopy currently on the market. However, they note that reimbursement may be a challenge in the widespread adoption of these technologies.<br /><br />Overall, the speaker provides an overview of the current status and potential benefits of AI in colonoscopy, focusing on its roles in polyp detection and characterization, regulatory approval, cost-effectiveness, and the availability of annotated video databases for training AI algorithms.
Keywords
artificial intelligence
AI
colonoscopy
automated polyp detection
CADe
automated polyp characterization
CADx
adenoma detection rates
regulatory approval
reimbursement
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