ReviewWorld journal of gastroenterology2021
Role of artificial intelligence in multidisciplinary imaging diagnosis of gastrointestinal diseases.
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 18 papers, 1 of them a synthesis 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Artificial intelligence-assisted endoscopic ultrasound in the diagnosis of gastrointestinal stromal tumors: a meta-analysis.Surgical endoscopy · 2023Pooled it
- An Alginate Hydrogel-Based Novel Oral Contrast Agent Designed for Gastric Computed Tomography Imaging.Chemical & biomedical imaging · 2026Article
- [Expert consensus on artificial intelligence-assisted data acquisition and clinical application in electronic nasopharyngolaryngoscopy].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2026Article
- Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine.World journal of gastroenterology · 2026Review
- Artificial intelligence in gastric cancer research: a bibliometric and visualized analysis from 1993 to 2026.Frontiers in oncology · 2026Review
- Emerging role of artificial intelligence in gastroenterology and hepatology.World journal of gastroenterology · 2025Review
- Concordance of ChatGPT artificial intelligence decision-making in colorectal cancer multidisciplinary meetings: retrospective study.BJS open · 2025Article
- The Many Faces of Intestinal Tumors in Adults, Including the Primary Role of CT Imaging in Emergencies and the Important Role of Cross-Sectional Imaging: A Pictorial Review.Healthcare (Basel, Switzerland) · 2025Review
- Rapid and Efficient Screening ofDiagnostics (Basel, Switzerland) · 2025Article
- Combining radiomics and deep learning to predict liver metastasis of gastric cancer on CT image.Frontiers in oncology · 2025Article
- Review
- Advancements in Barrett's esophagus detection: The role of artificial intelligence and its implications.World journal of gastroenterology · 2024Article
- Artificial intelligence applications in computed tomography in gastric cancer: a narrative review.Translational cancer research · 2023Review
- Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver.World journal of gastroenterology · 2023Review
- Artificial Intelligence-The Rising Star in the Field of Gastroenterology and Hepatology.Diagnostics (Basel, Switzerland) · 2023Review
- Unsupervised Learning Composite Network to Reduce Training Cost of Deep Learning Model for Colorectal Cancer Diagnosis.IEEE journal of translational engineering in health and medicine · 2023Article
- Artificial intelligence applications in gastroenterology: steps ahead.Medicine and pharmacy reports · 2021Article
- Artificial intelligence in gastrointestinal endoscopy: a comprehensive review.Annals of gastroenterologyReview
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 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of artificial intelligence-based tools is regarded as a promising approach to increase clinical efficiency in diagnostic imaging, improve the interpretability of results, and support decision-making for the detection and prevention of diseases. Radiology, endoscopy and pathology images are suitable for deep-learning analysis, potentially changing the way care is delivered in gastroenterology. The aim of this review is to examine the key aspects of different neural network architectures used for the evaluation of gastrointestinal conditions, by discussing how different models behave in critical tasks, such as lesion detection or characterization (
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.