ReviewDiagnostics (Basel, Switzerland)2019
Application of Artificial Intelligence in the Detection and Differentiation of Colon Polyps: A Technical Review for Physicians.
Review in Diagnostics (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 3 syntheses or guidelines pooled it, 41 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
- Performance and comparison of artificial intelligence and human experts in the detection and classification of colonic polyps.BMC gastroenterology · 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
- The Role of Computational Models in the Detection of Colorectal Carcinoma and Precancerous Lesions.International journal of molecular sciences · 2026Review
- Gastric Cancer Detection with Ensemble Learning on Digital Pathology: Use Case of Gastric Cancer on GasHisSDB Dataset.Diagnostics (Basel, Switzerland) · 2024Article
- Wireless capsule endoscopy multiclass classification using three-dimensional deep convolutional neural network model.Biomedical engineering online · 2023Article
- A New Approach for Gastrointestinal Tract Findings Detection and Classification: Deep Learning-Based Hybrid Stacking Ensemble Models.Diagnostics (Basel, Switzerland) · 2023Article
- Intraprocedure Artificial Intelligence Alert System for Colonoscopy Examination.Sensors (Basel, Switzerland) · 2023Article
- An AI-Based Colonic Polyp Classifier for Colorectal Cancer Screening Using Low-Dose Abdominal CT.Sensors (Basel, Switzerland) · 2022Article
- Development of artificial intelligence technology in diagnosis, treatment, and prognosis of colorectal cancer.World journal of gastrointestinal oncology · 2022Review
- Capsule Endoscopy: Pitfalls and Approaches to Overcome.Diagnostics (Basel, Switzerland) · 2021Review
- Artificial Intelligence in Colorectal Cancer Diagnosis Using Clinical Data: Non-Invasive Approach.Diagnostics (Basel, Switzerland) · 2021Article
- [Application of artificial intelligence for detection and classification of colon polyps].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2021Review
- The Future of Capsule Endoscopy: The Role of Artificial Intelligence and Other Technical Advancements.Clinical endoscopy · 2020Article
- Automated Classification of Colorectal Neoplasms in White-Light Colonoscopy Images via Deep Learning.Journal of clinical medicine · 2020Article
- Decision-Making in Artificial Intelligence: Is It Always Correct?Journal of Korean medical science · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Research in computer-aided diagnosis (CAD) and the application of artificial intelligence (AI) in the endoscopic evaluation of the gastrointestinal tract is novel. Since colonoscopy and detection of polyps can decrease the risk of colon cancer, it is recommended by multiple national and international societies. However, the procedure of colonoscopy is performed by humans where there are significant interoperator and interpatient variations, and hence, the risk of missing detection of adenomatous polyps. Early studies involving CAD and AI for the detection and differentiation of polyps show great promise. In this appraisal, we review existing scientific aspects of AI in CAD of colon polyps and discuss the pitfalls and future directions for advancing the science. This review addresses the technical intricacies in a manner that physicians can comprehend to promote a better understanding of this novel application.
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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.