ArticleClinical endoscopy2020
Artificial Intelligence in Gastrointestinal Endoscopy.
Article in Clinical endoscopy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05423964 (Impact of Artificial Intelligence on Trainee Adenoma Detection Rate), which is not on this map. Cited by 31 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Impact of Artificial Intelligence on Trainee Adenoma Detection Rate
Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Computer-Aided Diagnosis of Diminutive Colorectal Polyps in Endoscopic Images: Systematic Review and Meta-analysis of Diagnostic Test Accuracy.Journal of medical Internet research · 2021Pooled it
- AI-enabled multi-omics integration in colorectal cancer: from molecular stratification to clinical translation.Frontiers in cell and developmental biology · 2026Review
- Machine learning in gastrointestinal endoscopy: challenges and opportunities.BMJ open gastroenterology · 2025Review
- Review
- Multimodal AI in Biomedicine: Pioneering the Future of Biomaterials, Diagnostics, and Personalized Healthcare.Nanomaterials (Basel, Switzerland) · 2025Review
- Deep Learning-Based Semantic Segmentation for Objective Colonoscopy Quality Assessment.Journal of imaging · 2025Article
- Artificial intelligence in pancreatic cancer: diagnosis, limitations, and the future prospects-a narrative review.Journal of cancer research and clinical oncology · 2023Review
- Automated Detection of Bowel Preparation Scoring and Adequacy With Deep Convolutional Neural Networks.Journal of the Canadian Association of Gastroenterology · 2022Article
- Artificial Intelligence for Colonoscopy: Past, Present, and Future.IEEE journal of biomedical and health informatics · 2022Article
- Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy.Scientific reports · 2022Article
- Artificial Intelligence-Based Colorectal Polyp Histology Prediction: High Accuracy in Larger Polyps.Clinical endoscopy · 2022Article
- Assessment of the Risk of Severe Dengue Using Intrahost Viral Population in Dengue Virus Serotype 2 PatientsFrontiers in cellular and infection microbiology · 2022Article
- Choledochoscopy: An update.World journal of gastrointestinal endoscopy · 2021Review
- Digital surgery for gastroenterological diseases.World journal of gastroenterology · 2021Review
- Artificial Intelligence in Capsule Endoscopy: A Practical Guide to Its Past and Future Challenges.Diagnostics (Basel, Switzerland) · 2021Review
- Editors' Choice of Noteworthy Clinical Endoscopy Publications in the First Decade.Clinical endoscopy · 2021Article
- Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases.Diagnostics (Basel, Switzerland) · 2021Review
- Endoscopic diagnosis and treatment of gastric dysplasia and early cancer: Current evidence and what the future may hold.World journal of gastroenterology · 2021Review
- Deep neural network approaches for detecting gastric polyps in endoscopic images.Medical & biological engineering & computing · 2021Article
- Role of Artificial Intelligence in Video Capsule Endoscopy.Diagnostics (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly integrating into modern technology and clinical practice. Although in its nascency, AI has become a hot topic of investigation for applications in clinical practice. Multiple fields of medicine have embraced the possibility of a future with AI assisting in diagnosis and pathology applications. In the field of gastroenterology, AI has been studied as a tool to assist in risk stratification, diagnosis, and pathologic identification. Specifically, AI has become of great interest in endoscopy as a technology with substantial potential to revolutionize the practice of a modern gastroenterologist. From cancer screening to automated report generation, AI has touched upon all aspects of modern endoscopy. Here, we review landmark AI developments in endoscopy. Starting with broad definitions to develop understanding, we will summarize the current state of AI research and its potential applications. With innovation developing rapidly, this article touches upon the remarkable advances in AI-assisted endoscopy since its initial evaluation at the turn of the millennium, and the potential impact these AI models may have on the modern clinical practice. As with any discussion of new technology, its limitations must also be understood to apply clinical AI tools successfully.
Indexed as
Identifiers
What OpenQuestion holds
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.