Strengths and Weaknesses of an Artificial Intelligence Polyp Detection Program as Assessed by a High-Detecting Endoscopist

Article Gastroenterology & Hepatology

Effect of an artificial intelligence-based quality improvement system on efficacy of a computer-aided detection system in colonoscopy: a four-group parallel study

Liwen Yao et al.

Summary: This study evaluated the efficacy of combining the CADe and CAQ systems, showing that CAQ significantly improved the performance of CADe in improving the adenoma detection rate (ADR) in a four-group, parallel, controlled study.

ENDOSCOPY (2022)

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Article Gastroenterology & Hepatology

Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial)

Jeremy R. Glissen Brown et al.

Summary: In a U.S. multicenter tandem colonoscopy randomized controlled trial, the use of a CADe-system was shown to decrease AMR and SSL miss rate while increasing first-pass APC compared to HDWL colonoscopy alone.

CLINICAL GASTROENTEROLOGY AND HEPATOLOGY (2022)

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Editorial Material Gastroenterology & Hepatology

Flat colorectal adenocarcinoma: a worrisome false negative of artificial intelligence-assisted colonoscopy

Pierre Lafeuille et al.

ENDOSCOPY (2022)

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Article Gastroenterology & Hepatology

Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia

Michael B. Wallace et al.

Summary: This study demonstrates that the use of artificial intelligence can significantly reduce the miss rate of colorectal neoplasia, especially for small and subtle lesions. This is of great importance in improving the prevention of colorectal cancer.

GASTROENTEROLOGY (2022)

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Review Gastroenterology & Hepatology

Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis

Cesare Hassan et al.

Summary: The meta-analysis found that incorporating artificial intelligence as an aid for detecting colorectal neoplasia significantly increases the detection rate of colorectal neoplasia, independently of the main adenoma characteristics.

GASTROINTESTINAL ENDOSCOPY (2021)

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Article Gastroenterology & Hepatology

Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial

Shunsuke Kamba et al.

Summary: In a multicenter randomized controlled trial, it was found that the adenoma miss rate could be significantly reduced with CADe assistance based on deep learning, leading to a higher adenoma detection rate compared to standard colonoscopy.

JOURNAL OF GASTROENTEROLOGY (2021)

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Article Gastroenterology & Hepatology