SynthesisInternational journal of colorectal disease2021
Artificial intelligence (AI) real-time detection vs. routine colonoscopy for colorectal neoplasia: a meta-analysis and trial sequential analysis.
Synthesis in International journal of colorectal disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 3 of them syntheses that pooled it.
What it found
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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
29 citing papers in PubMed, 3 syntheses or guidelines pooled it, 49 citations in OpenAlex.
- A Systematic Review and Meta-analysis of Convolutional Neural Network in the Diagnosis of Colorectal Polyps and Cancer.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2023Pooled it
- Effect of artificial intelligence-aided colonoscopy for adenoma and polyp detection: a meta-analysis of randomized clinical trials.International journal of colorectal disease · 2022Pooled it
- Artificial Intelligence-Aid Colonoscopy Vs. Conventional Colonoscopy for Polyp and Adenoma Detection: A Systematic Review of 7 Discordant Meta-Analyses.Frontiers in medicine · 2021Pooled it
- The Addition of Computer-Aided Detection (CADe) to Texture and Color Enhancement Imaging (TXI) Does Not Improve Adenoma Detection Rate During Colonoscopy: A Prospective Study.Journal of gastroenterology and hepatology · 2026Trial
- Effectiveness of AI-enhanced colonoscopy: A case-control study using real world evidence in a young screening age population.Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association · 2026Article
- Artificial intelligence in colonoscopy: Enhancing quality indicators for optimal patient outcomes.World journal of gastroenterology · 2025Review
- [Role of Artificial Intelligence in Improving Quality of Colonoscopy].The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi · 2025Review
- Innovative approaches in colorectal cancer screening: advances in detection methods and the role of artificial intelligence.Therapeutic advances in gastroenterology · 2025Review
- Patient Perspective of Use of Artificial Intelligence During Colonoscopy.Gastro hep advances · 2025Review
- Exploring human-artificial intelligence interactions in a negative pragmatic trial of computer-aided polyp detection.iGIE : innovation, investigation and insights · 2024Article
- Artificial intelligence in screening and diagnosis of surgical diseases: A narrative review.AIMS public health · 2024Review
- 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
- Automated Segmentation of Optical Coherence Tomography Images of the Human Tympanic Membrane Using Deep Learning.Algorithms · 2023Article
- Advances in artificial intelligence and computer science for computer-aided diagnosis of colorectal polyps: current status.Endoscopy international open · 2023Review
- Artificial Intelligence and Cancer Control: Toward Prioritizing Justice, Equity, Diversity, and Inclusion (JEDI) in Emerging Decision Support Technologies.Current oncology reports · 2023Review
- Review
- Quality of bowel preparation in patients with inflammatory bowel disease undergoing colonoscopy: What factors to consider?World journal of gastrointestinal endoscopy · 2023Review
- Novel artificial intelligence-enabled deep learning system to enhance adenoma detection: a prospective randomized controlled study.iGIE : innovation, investigation and insights · 2023Article
- The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
GOALS AND
backgroundStudies analyzing artificial intelligence (AI) in colonoscopies have reported improvements in detecting colorectal cancer (CRC) lesions, however its utility in the realworld remains limited. In this systematic review and meta-analysis, we evaluate the efficacy of AI-assisted colonoscopies against routine colonoscopy (RC). STUDY: We performed an extensive search of major databases (through January 2021) for randomized controlled trials (RCTs) reporting adenoma and polyp detection rates. Odds ratio (OR) and standardized mean differences (SMD) with 95% confidence intervals (CIs) were reported. Additionally, trial sequential analysis (TSA) was performed to guard against errors.
resultsSix RCTs were included (4996 participants). The mean age (SD) was 51.99 (4.43) years, and 49% were females. Detection rates favored AI over RC for adenomas (OR 1.77; 95% CI: 1.570-2.08) and polyps (OR 1.91; 95% CI: 1.68-2.16). Secondary outcomes including mean number of adenomas (SMD 0.23; 95% CI: 0.18-0.29) and polyps (SMD 0.23; 95% CI: 0.17-0.29) detected per procedure favored AI. However, RC outperformed AI in detecting pedunculated polyps. Withdrawal times (WTs) favored AI when biopsies were included, while WTs without biopsies, cecal intubation times, and bowel preparation adequacy were similar.
conclusionsColonoscopies equipped with AI detection algorithms could significantly detect previously missed adenomas and polyps while retaining the ability to self-assess and improve periodically. More effective clearance of diminutive adenomas may allow lengthening in surveillance intervals, reducing the burden of surveillance colonoscopies, and increasing its accessibility to those at higher risk. TSA ruled out the risk for false-positive results and confirmed a sufficient sample size to detect the observed effect. Currently, these findings suggest that AI-assisted colonoscopy can serve as a useful proxy to address critical gaps in CRC identification.
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Registered trials
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.