ReviewWorld journal of gastrointestinal endoscopy2025
Revolutionizing upper gastrointestinal disease diagnosis: The transformative role of artificial intelligence in endoscopy.
Review in World journal of gastrointestinal endoscopy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Machine learning applications in the detection and treatment of esophageal cancer.Discover oncology · 2026Review
- Artificial Intelligence in Gastrointestinal Endoscopy and Hemostatic Decision-Making: Current Evidence, Clinical Implications and Implementation Barriers.Life (Basel, Switzerland) · 2026Review
- Bridging the gap between AI and traditional teaching methods in medical education: opportunities, challenges, and solutions.Frontiers in medicine · 2026Review
- A YOLO Ensemble Framework for Detection of Barrett's Esophagus Lesions in Endoscopic Images.Diagnostics (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rapid advancement of technology, artificial intelligence (AI) has emerged as a transformative force in gastroenterology, particularly in diagnosing upper gastrointestinal diseases such as Barrett's esophagus (BE), esophageal cancer, gastroesophageal reflux disease (GERD), and esophagogastric varices. AI's capabilities in image analysis, classification, detection, and segmentation have significantly improved diagnostic accuracy and efficiency. For BE, AI models achieve high sensitivity and specificity in detecting early neoplastic changes and guiding targeted biopsies. In esophageal cancer, AI enhances early lesion detection, improving intervention success rates. For GERD, AI classifies disease severity based on the Los Angeles grading system and accurately segments lesions. Additionally, AI detects esophagogastric varices and predicts bleeding risks more effectively than traditional methods. Despite these advancements, challenges remain, including the need for high-quality data, multi-center validation, and ensuring AI model interpretability. Future research should address these issues and further integrate AI into clinical practice to optimize patient outcomes. This review highlights AI's transformative impact on upper gastrointestinal disease diagnosis, emphasizing its potential to revolutionize endoscopic practice and improve patient care.
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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.