ReviewWorld journal of gastroenterology2021
Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions.
Review in World journal of gastroenterology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 50 citations in OpenAlex.
- A novel prognostic model for colon adenocarcinoma based on cofactor and vitamin metabolism-related genes.Translational cancer research · 2026Article
- Review
- SpectraNet: a novel model for polyp segmentation leveraging a spectral-guided mixture of functional experts.Frontiers in oncology · 2026Article
- Collagen disorder architecture features are associated with clinical, molecular, genetic factors and survival outcomes in colon cancer.NPJ precision oncology · 2025Article
- Synthetic Data-augmented Explainable Vision Transformer for Colorectal Cancer Diagnosis via Surface Tactile Imaging.Engineering applications of artificial intelligence · 2025Article
- A Narrative Review on the Role of Artificial Intelligence (AI) in Colorectal Cancer Management.Cureus · 2025Review
- Identification of PANoptosis associated lncRNAs associated with clinical prognosis and immune infiltration microenvironment in colon adenocarcinoma.Discover oncology · 2025Article
- Article
- Deep learning-based classification of colorectal cancer in histopathology images for category detection.Biology methods & protocols · 2025Article
- ERCPMP: an endoscopic image and video dataset for colorectal polyps morphology and pathology.BMC research notes · 2024Article
- Revolutionizing Gastrointestinal Disorder Management: Cutting-Edge Advances and Future Prospects.Journal of clinical medicine · 2024Review
- How AI and Robotics Will Advance Interventional Radiology: Narrative Review and Future Perspectives.Diagnostics (Basel, Switzerland) · 2024Review
- Establishment of disulfidptosis-related LncRNA signature as biomarkers in colon adenocarcinoma.Cancer cell international · 2024Article
- Establishment and validation of an artificial intelligence-based model for real-time detection and classification of colorectal adenoma.Scientific reports · 2024Article
- Colorectal Cancer Diagnosis through Breath Test Using a Portable Breath Analyzer-Preliminary Data.Sensors (Basel, Switzerland) · 2024Article
- Comparative Analysis of Machine Learning Models for Image Detection of Colonic Polyps vs. Resected Polyps.Journal of imaging · 2023Article
- Negative Samples for Improving Object Detection-A Case Study in AI-Assisted Colonoscopy for Polyp Detection.Diagnostics (Basel, Switzerland) · 2023Article
- Intraprocedure Artificial Intelligence Alert System for Colonoscopy Examination.Sensors (Basel, Switzerland) · 2023Article
- Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect.Frontiers in medicine · 2023Review
- Magnetic Levitation of Personalized Nanoparticle-Protein Corona as an Effective Tool for Cancer Detection.Nanomaterials (Basel, Switzerland) · 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
5 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular tissue (adenomatous polyps) is detected early. Colonoscopy has been strongly recommended as a screening test for both early cancer and adenomatous polyps. However, it has some limitations that include the high polyp miss rate for smaller (< 10 mm) or flat polyps, which are easily missed during visual inspection. Due to the rapid advancement of technology, artificial intelligence (AI) has been a thriving area in different fields, including medicine. Particularly, in gastroenterology AI software has been included in computer-aided systems for diagnosis and to improve the assertiveness of automatic polyp detection and its classification as a preventive method for CRC. This article provides an overview of recent research focusing on AI tools and their applications in the early detection of CRC and adenomatous polyps, as well as an insightful analysis of the main advantages and misconceptions in the field.
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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.