ArticleGastroenterology report2023
Artificial intelligence empowers the second-observer strategy for colonoscopy: a randomized clinical trial.
Article in Gastroenterology report, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.
- The role of artificial intelligence in adenoma detection during colonoscopy: a systematic review and meta-analysis of randomized controlled trials-Artificial intelligence and adenoma detection.Techniques in coloproctology · 2026Pooled it
- Comparative Performance of Artificial Intelligence-Based Computer-Aided Detection Systems for Colorectal Polyps: A Systematic Review and Network Meta-Analysis.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Pooled it
- Exploring Real-Time Tracking of Vocal Fold Polyps in Video-Stroboscopy Using Deep Learning.The Laryngoscope · 2026Article
- Computer-aided polyp detection and characterisation systems to support colonoscopy: a systematic review with results stratified by each individual artificial intelligence system.BMJ digital health & AI · 2026Article
- Advanced computer-aided detection system exhibits no more false positives than experienced endoscopists in an image-based comparative study of colon polyps.Frontiers in medicine · 2026Article
- Asia-Pacific consensus on the use of artificial intelligence in colorectal cancer screening and surveillance.iGIE : innovation, investigation and insights · 2025Article
- The implementation of computer-aided detection in an initial endoscopy training improves the quality measures of trainees' future colonoscopies: a retrospective cohort study.Surgical endoscopy · 2025Article
- [Role of Artificial Intelligence in Improving Quality of Colonoscopy].The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi · 2025Review
- PolyDeep Advance 1: Clinical Validation of a Computer-Aided Detection System for Colorectal Polyp Detection with a Second Observer Design.Diagnostics (Basel, Switzerland) · 2025Article
- Deep learning-assisted colonoscopy images for prediction of mismatch repair deficiency in colorectal cancer.Surgical endoscopy · 2025Article
- Review
- Concordance with CONSORT-AI guidelines in reporting of randomised controlled trials investigating artificial intelligence in oncology: a systematic review.BMJ oncology · 2025Article
- Advances in colorectal cancer screening: technological innovations, guideline discrepancies, and individualized strategies.Frontiers in oncology · 2025Review
- Single Versus Second Observer vs Artificial Intelligence to Increase the ADENOMA Detection Rate of Colonoscopy-A Network Analysis.Digestive diseases and sciences · 2024Article
- Development and external validation of a transfer learning-based system for the pathological diagnosis of colorectal cancer: a large emulated prospective study.Frontiers in oncology · 2024Article
- Artificial intelligence for colorectal neoplasia detection during colonoscopy: a systematic review and meta-analysis of randomized clinical trials.EClinicalMedicine · 2023Article
- The Role of Artificial Intelligence in Colorectal Cancer Screening: Lesion Detection and Lesion Characterization.Cancers · 2023Review
- Effectiveness of CADe in Colonoscopy for Improved Adenoma and Polyp Detection Under Diverse Clinical Conditions.In vivo (Athens, Greece)Article
Corrections and comments
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Authors and funding
14 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: In colonoscopy screening for colorectal cancer, human vision limitations may lead to higher miss rate of lesions; artificial intelligence (AI) assistance has been demonstrated to improve polyp detection. However, there still lacks direct evidence to demonstrate whether AI is superior to trainees or experienced nurses as a second observer to increase adenoma detection during colonoscopy. In this study, we aimed to compare the effectiveness of assistance from AI and human observer during colonoscopy. Methods: A prospective multicenter randomized study was conducted from 2 September 2019 to 29 May 2020 at four endoscopy centers in China. Eligible patients were randomized to either computer-aided detection (CADe)-assisted group or observer-assisted group. The primary outcome was adenoma per colonoscopy (APC). Secondary outcomes included polyp per colonoscopy (PPC), adenoma detection rate (ADR), and polyp detection rate (PDR). We compared continuous variables and categorical variables by using R studio (version 3.4.4). Results: A total of 1,261 (636 in the CADe-assisted group and 625 in the observer-assisted group) eligible patients were analysed. APC (0.42 vs 0.35, Conclusions: Compared with the human observer, the CADe system may improve the clinical outcome of colonoscopy and reduce disturbance to routine practice (Chictr.org.cn No.: ChiCTR1900025235).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.