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The Impacts of Computer-Aided Detection of Colorectal Polyps on Subsequent Colonoscopy Surveillance Intervals: Simulation Study

The Impacts of Computer-Aided Detection of Colorectal Polyps on Subsequent Colonoscopy Surveillance Intervals: Simulation Study

Advanced adenomas were defined as adenomas ≥10 mm in diameter, with villous histology in at least 25% of the adenoma, or high-grade dysplasia or carcinoma. The advanced serrated polyp was defined as a sessile serrated polyp with dysplasia, or ≥10 mm in diameter, or a traditional serrated adenoma.

Ka Luen Thomas Lui, Sze Hang Kevin Liu, Kathy Leung, Joseph T Wu, Ann G Zauber, Wai Keung Leung

J Med Internet Res 2023;25:e42665

Natural Language Processing for Assessing Quality Indicators in Free-Text Colonoscopy and Pathology Reports: Development and Usability Study

Natural Language Processing for Assessing Quality Indicators in Free-Text Colonoscopy and Pathology Reports: Development and Usability Study

While all the indicators are important, the adenoma detection rate (ADR) and sessile serrated lesion (SSL) detection rate (SDR) of endoscopists are well-established key indicators of postcolonoscopy colorectal cancer incidence and related deaths [5-7]. Another crucial quality indicator is the adherence to guidelines for setting the frequency of follow-up colonoscopies, known as the surveillance interval.

Jung Ho Bae, Hyun Wook Han, Sun Young Yang, Gyuseon Song, Soonok Sa, Goh Eun Chung, Ji Yeon Seo, Eun Hyo Jin, Heecheon Kim, DongUk An

JMIR Med Inform 2022;10(4):e35257

Can Real-time Computer-Aided Detection Systems Diminish the Risk of Postcolonoscopy Colorectal Cancer?

Can Real-time Computer-Aided Detection Systems Diminish the Risk of Postcolonoscopy Colorectal Cancer?

The adenoma detection rate (ADR) is regarded as an important marker of the quality of inspection in colonoscopy. The identification and removal of adenomatous polyps are considered to be important in CRC prevention [1,2]. More recently, computer-aided detection (CADe) tools that incorporate a 3 D fully convolutional network have been developed to aid with colonoscopy screening for CRC.

Mariusz Madalinski, Roger Prudham

JMIR Med Inform 2021;9(12):e25328