ReviewEndoscopic ultrasound
Application of artificial intelligence for diagnosis of pancreatic ductal adenocarcinoma by EUS: A systematic review and meta-analysis.
Review in Endoscopic ultrasound. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 4 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
19 citing papers in PubMed, 4 syntheses or guidelines pooled it, 28 citations in OpenAlex.
- Artificial Intelligence Performance in Image-Based Cancer Identification: Umbrella Review of Systematic Reviews.Journal of medical Internet research · 2025Pooled it
- Diagnostic performance of AI-assisted endoscopy diagnosis of digestive system tumors: an umbrella review.Frontiers in oncology · 2025Pooled it
- Artificial intelligence-assisted endoscopic ultrasound in the diagnosis of gastrointestinal stromal tumors: a meta-analysis.Surgical endoscopy · 2023Pooled it
- Application of artificial intelligence in the diagnosis of subepithelial lesions using endoscopic ultrasonography: a systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Letter to the Editor: Reconsidering relevance of endoscopic ultrasound-guided radiofrequency ablation in pancreatic cancer treatment: Future perspectives on artificial intelligence.World journal of radiology · 2026Article
- VEA-net: vascular enhancement attention with dual-backbone multi-task learning for comprehensive ROP management across multi-center datasets.Frontiers in cell and developmental biology · 2026Article
- Artificial intelligence in endoscopic ultrasound for lymph node diagnosis: perspective on an evolving frontier.Clinical endoscopy · 2025Article
- Guarding against digestive-system cancers: Unveiling the role of Chk2 as a potential therapeutic target.Genes & diseases · 2025Review
- Artificial Intelligence-Assisted Endoscopy in Diagnosis of Gastrointestinal Tumors: A Review of Systematic Reviews and Meta-Analyses.Gastro hep advances · 2025Review
- Applications of Artificial Intelligence-Based Systems in the Management of Esophageal Varices.Journal of personalized medicine · 2024Review
- The Immune Landscape of Pheochromocytoma and Paraganglioma: Current Advances and Perspectives.Endocrine reviews · 2024Review
- Diagnostic Endoscopic Ultrasound (EUS) of the Luminal Gastrointestinal Tract.Diagnostics (Basel, Switzerland) · 2024Review
- Role of Artificial Intelligence in Endoscopic Intervention: A Clinical Review.Journal of community hospital internal medicine perspectives · 2024Review
- Role of Endoscopic Ultrasound in Diagnosis of Pancreatic Ductal Adenocarcinoma.Diagnostics (Basel, Switzerland) · 2023Review
- Non-enhanced magnetic resonance imaging-based radiomics model for the differentiation of pancreatic adenosquamous carcinoma from pancreatic ductal adenocarcinoma.Frontiers in oncology · 2023Article
- Advances in biomarkers and techniques for pancreatic cancer diagnosis.Cancer cell international · 2022Review
- A multimodal artificial intelligence system for the detection and diagnosis of solid pancreatic lesions under EUS.Endoscopic ultrasoundArticle
- Enhancing gastrointestinal stromal tumor risk stratification: A novel deep learning approach applied to EUS imaging.Endoscopic ultrasoundArticle
- The application of artificial intelligence in EUS.Endoscopic ultrasoundReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
EUS-guided tissue acquisition carries certain risks from unnecessary needle puncture in the low-likelihood lesions. Artificial intelligence (AI) system may enable us to resolve these limitations. We aimed to assess the performance of AI-assisted diagnosis of pancreatic ductal adenocarcinoma (PDAC) by off-line evaluating the EUS images from different modes. The databases PubMed, EMBASE, SCOPUS, ISI, IEEE, and Association for Computing Machinery were systematically searched for relevant studies. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic curve were estimated using R software. Of 369 publications, 8 studies with a total of 870 PDAC patients were included. The pooled sensitivity and specificity of AI-assisted EUS were 0.91 (95% confidence interval [CI], 0.87-0.93) and 0.90 (95% CI, 0.79-0.96), respectively, with DOR of 81.6 (95% CI, 32.2-207.3), for diagnosis of PDAC. The area under the curve was 0.923. AI-assisted B-mode EUS had pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 0.91, 0.90, 0.94, and 0.84, respectively; while AI-assisted contrast-enhanced EUS and AI-assisted EUS elastography had sensitivity, specificity, PPV, and NPV of 0.95, 0.95, 0.97, and 0.90; and 0.88, 0.83, 0.96 and 0.57, respectively. AI-assisted EUS has a high accuracy rate and may potentially enhance the performance of EUS by aiding the endosonographers to distinguish PDAC from other solid lesions. Validation of these findings in other independent cohorts and improvement of AI function as a real-time diagnosis to guide for tissue acquisition are warranted.
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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.