ReviewDiagnostics (Basel, Switzerland)2020
The Role of Artificial Intelligence in Endoscopic Ultrasound for Pancreatic Disorders.
Review in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05151939 (Endoscopic Ultrasound), which is not on this map. Cited by 18 papers.
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.
Endoscopic Ultrasound (EUS) Assessment of Normal Mediastinal and Abdominal Organ/Anatomic Strictures Using a Novel Developed Artificial Intelligence Model
Who cites it
18 citing papers in PubMed.
- Article
- Review
- Emerging role of artificial intelligence in gastroenterology and hepatology.World journal of gastroenterology · 2025Review
- Linear endoscopic ultrasound: Current uses and future perspectives in mediastinal examination.World journal of gastroenterology · 2024Article
- Computed tomography-based prediction of pancreatitis following biliary metal stent placement with the convolutional neural network.Endoscopy international open · 2024Article
- Smart Endoscopy Is Greener Endoscopy: Leveraging Artificial Intelligence and Blockchain Technologies to Drive Sustainability in Digestive Health Care.Diagnostics (Basel, Switzerland) · 2023Review
- Artificial Intelligence in Endoscopic Ultrasonography-Guided Fine-Needle Aspiration/Biopsy (EUS-FNA/B) for Solid Pancreatic Lesions: Opportunities and Challenges.Diagnostics (Basel, Switzerland) · 2023Review
- Applications and Prospects of Artificial Intelligence-Assisted Endoscopic Ultrasound in Digestive System Diseases.Diagnostics (Basel, Switzerland) · 2023Review
- Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver.World journal of gastroenterology · 2023Review
- Deep Learning for Automatic Differentiation of Mucinous versus Non-Mucinous Pancreatic Cystic Lesions: A Pilot Study.Diagnostics (Basel, Switzerland) · 2022Article
- Enhanced endoscopic ultrasound imaging for pancreatic lesions: The road to artificial intelligence.World journal of gastroenterology · 2022Review
- Current role of endoscopic ultrasound in the diagnosis and management of pancreatic cancer.World journal of gastrointestinal endoscopy · 2022Review
- Application of artificial intelligence in diagnosis of pancreatic malignancies by endoscopic ultrasound: a systemic review.Therapeutic advances in gastroenterology · 2022Review
- Artificial intelligence in gastroenterology: A state-of-the-art review.World journal of gastroenterology · 2021Review
- A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology.Diagnostics (Basel, Switzerland) · 2021Review
- Pooled diagnostic parameters of artificial intelligence in EUS image analysis of the pancreas: A descriptive quantitative review.Endoscopic ultrasoundReview
- Artificial intelligence: The new wave of innovation in EUS.Endoscopic ultrasoundArticle
- [The Era of Intelligent Endoscopy: How Artificial Intelligence Empowers Digestive Endoscopy].Acta gastroenterologica LatinoamericanaReview
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of artificial intelligence (AI) in various medical imaging applications has expanded remarkably, and several reports have focused on endoscopic ultrasound (EUS) images of the pancreas. This review briefly summarizes each report in order to help endoscopists better understand and utilize the potential of this rapidly developing AI, after a description of the fundamentals of the AI involved, as is necessary for understanding each study. At first, conventional computer-aided diagnosis (CAD) was used, which extracts and selects features from imaging data using various methods and introduces them into machine learning algorithms as inputs. Deep learning-based CAD utilizing convolutional neural networks has been used; in these approaches, the images themselves are used as inputs, and more information can be analyzed in less time and with higher accuracy. In the field of EUS imaging, although AI is still in its infancy, further research and development of AI applications is expected to contribute to the role of optical biopsy as an alternative to EUS-guided tissue sampling while also improving diagnostic accuracy through double reading with humans and contributing to EUS education.
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.