ArticleScientific reports2019
Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05611151 (Real-time Computer-Aided Detection of Colonic Adenomas With NEC WISE VISION® Endoscopy), which is not on this map. Cited by 106 papers, 8 of them syntheses 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.
Real-time Computer-Aided Detection of Colonic Adenomas With NEC WISE VISION® Endoscopy: Prospective, Randomized Clinical Performance Evaluation
Who cites it
106 citing papers in PubMed, 8 syntheses or guidelines pooled it, 258 citations in OpenAlex.
- Effect of AI-assisted diagnosis on adenomas of different sizes: a meta-analysis with evidence from RCTs and trial sequential analysis.BMC gastroenterology · 2025Pooled it
- Artificial intelligence in endoscopy and colonoscopy: a comprehensive bibliometric analysis of global research trends.Frontiers in medicine · 2025Pooled it
- Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review.Journal of medical systems · 2024Pooled it
- 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
- Computer-aided anatomy recognition in intrathoracic and -abdominal surgery: a systematic review.Surgical endoscopy · 2022Pooled it
- Visualizing knowledge evolution trends and research hotspots of artificial intelligence in colorectal cancer: A bibliometric analysis.Frontiers in oncology · 2022Pooled it
- Diagnostic Accuracy of Artificial Intelligence and Computer-Aided Diagnosis for the Detection and Characterization of Colorectal Polyps: Systematic Review and Meta-analysis.Journal of medical Internet research · 2021Pooled it
- Pooled it
- The Role of Computational Models in the Detection of Colorectal Carcinoma and Precancerous Lesions.International journal of molecular sciences · 2026Review
- Article
- Real-Time Endoscopic Video Enhancement via Degradation Representation Estimation and Propagation.Journal of imaging · 2026Article
- SIG-CFFNet: Structural Information-Guided Cascaded Feature Fusion Network for Gastrointestinal Anatomy Classification.Annals of biomedical engineering · 2026Article
- Integration of Endocuff-Assisted and Computer-Aided Colonoscopy: A Meta-Analysis of Randomized Controlled Trials.JGH open : an open access journal of gastroenterology and hepatology · 2026Review
- Three-Dimensional Visualization and Detection of the Pulmonary Venous-Left Atrium Connection Using Artificial Intelligence in Fetal Cardiac Ultrasound Screening.Bioengineering (Basel, Switzerland) · 2026Article
- Expected Values of Artificial Intelligence in Colon Capsule Endoscopy: Artificial Intelligence in Capsule Endoscopy Consortium Position Statement.Endoscopy international open · 2026Article
- AI-enabled multi-omics integration in colorectal cancer: from molecular stratification to clinical translation.Frontiers in cell and developmental biology · 2026Review
- Advancing Real-Time Polyp Detection in Colonoscopy Imaging: An Anchor-Free Deep Learning Framework with Adaptive Multi-Scale Perception.Sensors (Basel, Switzerland) · 2025Article
- Role of artificial intelligence in the detection and characterization of gastrointestinal premalignant and early malignant lesions.World journal of gastroenterology · 2025Review
- Machine learning in gastrointestinal endoscopy: challenges and opportunities.BMJ open gastroenterology · 2025Review
- Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives.European journal of medical research · 2025Review
46 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gaps in colonoscopy skills among endoscopists, primarily due to experience, have been identified, and solutions are critically needed. Hence, the development of a real-time robust detection system for colorectal neoplasms is considered to significantly reduce the risk of missed lesions during colonoscopy. Here, we develop an artificial intelligence (AI) system that automatically detects early signs of colorectal cancer during colonoscopy; the AI system shows the sensitivity and specificity are 97.3% (95% confidence interval [CI] = 95.9%-98.4%) and 99.0% (95% CI = 98.6%-99.2%), respectively, and the area under the curve is 0.975 (95% CI = 0.964-0.986) in the validation set. Moreover, the sensitivities are 98.0% (95% CI = 96.6%-98.8%) in the polypoid subgroup and 93.7% (95% CI = 87.6%-96.9%) in the non-polypoid subgroup; To accelerate the detection, tensor metrics in the trained model was decomposed, and the system can predict cancerous regions 21.9 ms/image on average. These findings suggest that the system is sufficient to support endoscopists in the high detection against non-polypoid lesions, which are frequently missed by optical colonoscopy. This AI system can alert endoscopists in real-time to avoid missing abnormalities such as non-polypoid polyps during colonoscopy, improving the early detection of this disease.
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.