Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience

2018/04/10 by Masashi Misawa, Shin-ei Kudo, Shin‐ei Kudo +23 · 397 citations
Medicine · #Artificial intelligence #Cancer #Colonoscopy #Colorectal Cancer Screening and Detection #Colorectal cancer #Computer science #Esophageal Cancer Research and Treatment #Gastric Cancer Management and Outcomes #General surgery #Internal medicine #Medicine

paper · doi:10.1053/j.gastro.2018.04.003

published in Gastroenterology 154(8), 2027-2029.e3 (Elsevier BV)

openalex publication_date 2018/04/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30

Abstract

The adenoma detection rate is an established quality indicator for colonoscopy. For instance, a 1% increase in the adenoma detection rate was associated with a 3% decrease in interval colorectal cancer incidence.1 However, a previous meta-analysis showed that approximately 26% of neoplastic diminutive polyps were missed in single colonoscopy.2 Two factors are considered to affect this rate; one is blind spots and the other is human error. The first factor could be solved using a wide-angle scope or distal attachments, but human error is not easily overcome.

Citations

• Polyp Miss Rate Determined by Tandem Colonoscopy: A Systematic Review

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