ReviewDiagnostics (Basel, Switzerland)2021
Computer-Aided Detection False Positives in Colonoscopy.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- Computer-assisted detection of colorectal polyps: a narrative review of clinical utility, ongoing limitations, and opportunities for advancement.Translational gastroenterology and hepatology · 2026Review
- Development of an Artificial Intelligence for Detecting False Positive Detection to Manage the Accuracy of Artificial Intelligence in Colonoscopy.Journal of the anus, rectum and colon · 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
- Multimodal generative AI for interpreting 3D medical images and videos.NPJ digital medicine · 2025Review
- A comparative study benchmarking colon polyp with computer-aided detection (CADe) software.DEN open · 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
- A prospective comparison of two computer aided detection systems with different false positive rates in colonoscopy.NPJ digital medicine · 2024Article
- Long-term impact of artificial intelligence on colorectal adenoma detection in high-risk colonoscopy.World journal of gastrointestinal endoscopy · 2024Article
- Human-artificial intelligence interaction in gastrointestinal endoscopy.World journal of gastrointestinal endoscopy · 2024Review
- Assessing clinical efficacy of polyp detection models using open-access datasets.Frontiers in oncology · 2024Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
Randomized control trials and meta-analyses comparing colonoscopies with and without computer-aided detection (CADe) assistance showed significant increases in adenoma detection rates (ADRs) with CADe. A major limitation of CADe is its false positives (FPs), ranked 3rd in importance among 59 research questions in a modified Delphi consensus review. The definition of FPs varies. One commonly used definition defines an FP as an activation of the CADe system, irrespective of the number of frames or duration of time, not due to any polypoid or nonpolypoid lesions. Although only 0.07 to 0.2 FPs were observed per colonoscopy, video analysis studies using FPs as the primary outcome showed much higher numbers of 26 to 27 per colonoscopy. Most FPs were of short duration (91% < 0.5 s). A higher number of FPs was also associated with suboptimal bowel preparation. The appearance of FPs can lead to user fatigue. The polypectomy of FPs results in increased procedure time and added use of resources. Re-training the CADe algorithms is one way to reduce FPs but is not practical in the clinical setting during colonoscopy. Water exchange (WE) is an emerging method that the colonoscopist can use to provide salvage cleaning during insertion. We discuss the potential of WE for reducing FPs as well as the augmentation of ADRs through CADe.
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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.