ReviewTranslational gastroenterology and hepatology2021
Artificial intelligence and computer-aided diagnosis for colonoscopy: where do we stand now?
Review in Translational gastroenterology and hepatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis 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
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Computer-aided diagnosis for colorectal polyp in comparison with endoscopists: Systematic review and meta-analysis.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2025Pooled it
- The Role of Computational Models in the Detection of Colorectal Carcinoma and Precancerous Lesions.International journal of molecular sciences · 2026Review
- Colorectal cancer unmasked: A synergistic AI framework for Hyper-granular image dissection, precision segmentation, and automated diagnosis.BMC medical imaging · 2025Article
- PolyDeep Advance 1: Clinical Validation of a Computer-Aided Detection System for Colorectal Polyp Detection with a Second Observer Design.Diagnostics (Basel, Switzerland) · 2025Article
- Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.Scientific reports · 2025Article
- A hybrid framework for colorectal cancer detection and U-Net segmentation using polynetDWTCADx.Scientific reports · 2025Article
- Advances in endoscopic diagnosis and management of colorectal cancer.World journal of gastrointestinal oncology · 2024Article
- Colorectal cancer histopathology image analysis: A comparative study of prognostic values of automatically extracted morphometric nuclear features in multispectral and red-blue-green imagery.Histology and histopathology · 2024Article
- Bridging the Diagnostic Gap between Histopathologic and Hysteroscopic Chronic Endometritis with Deep Learning Models.Medicina (Kaunas, Lithuania) · 2024Review
- Exploring human-artificial intelligence interactions in a negative pragmatic trial of computer-aided polyp detection.iGIE : innovation, investigation and insights · 2024Article
- The Impacts of Computer-Aided Detection of Colorectal Polyps on Subsequent Colonoscopy Surveillance Intervals: Simulation Study.Journal of medical Internet research · 2023Article
- Image enhanced colonoscopy: updates and prospects-a review.Translational gastroenterology and hepatology · 2023Review
- Experimental evidence of effective human-AI collaboration in medical decision-making.Scientific reports · 2022Article
- Videomics of the Upper Aero-Digestive Tract Cancer: Deep Learning Applied to White Light and Narrow Band Imaging for Automatic Segmentation of Endoscopic Images.Frontiers in oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computer-aided diagnosis (CAD) for colonoscopy with use of artificial intelligence (AI) is catching increased attention of endoscopists. CAD allows automated detection and pathological prediction, namely optical biopsy, of colorectal polyps during real-time endoscopy, which help endoscopists avoid missing and/or misdiagnosing colorectal lesions. With the increased number of publications in this field and emergence of the AI medical device that have already secured regulatory approval, CAD in colonoscopy is now being implemented into clinical practice. On the other side, drawbacks and weak points of CAD in colonoscopy have not been thoroughly discussed. In this review, we provide an overview of CAD for optical biopsy of colorectal lesions with a particular focus on its clinical applications and limitations.
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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.