ArticleScientific reports2022
Efficacy of ultrasound endoscopy with artificial intelligence for the differential diagnosis of non-gastric gastrointestinal stromal tumors.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- [Current status and challenges of artificial intelligence and organoid technologies in precision diagnosis and treatment of gastrointestinal stromal tumors].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026Review
- Artificial intelligence-assisted endoscopic ultrasound diagnosis of esophageal subepithelial lesions.Surgical endoscopy · 2025Article
- An artificial intelligence model utilizing endoscopic ultrasonography for differentiating small and micro gastric stromal tumors from gastric leiomyomas.BMC gastroenterology · 2025Article
- A Lightweight Machine Learning Model for High Precision Gastrointestinal Stromal Tumors Identification.Bioengineering (Basel, Switzerland) · 2025Article
- Application of AI in the identification of gastrointestinal stromal tumors: a comprehensive analysis based on pathological, radiological, and genetic variation features.Frontiers in genetics · 2025Review
- Endoscopic Ultrasound and Gastric Sub-Epithelial Lesions: Ultrasonographic Features, Tissue Acquisition Strategies, and Therapeutic Management.Medicina (Kaunas, Lithuania) · 2024Review
- Applications and Prospects of Artificial Intelligence-Assisted Endoscopic Ultrasound in Digestive System Diseases.Diagnostics (Basel, Switzerland) · 2023Review
- Endoscopic ultrasound artificial intelligence-assisted for prediction of gastrointestinal stromal tumors diagnosis: A systematic review and meta-analysis.World journal of gastrointestinal endoscopy · 2023Article
- Natural Course of Asymptomatic Upper Gastrointestinal Subepithelial Lesion of 2 cm or Less in Size.Journal of clinical medicine · 2022Article
- [The Era of Intelligent Endoscopy: How Artificial Intelligence Empowers Digestive Endoscopy].Acta gastroenterologica LatinoamericanaReview
- Enhancing gastrointestinal stromal tumor risk stratification: A novel deep learning approach applied to EUS imaging.Endoscopic ultrasoundArticle
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Authors and funding
14 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastrointestinal stromal tumors (GISTs) are common subepithelial lesions (SELs) and require treatment considering their malignant potential. We recently developed an endoscopic ultrasound-based artificial intelligence (EUS-AI) system to differentiate GISTs from non-GISTs in gastric SELs, which were used to train the system. We assessed whether the EUS-AI system designed for diagnosing gastric GISTs could be applied to non-gastric GISTs. Between January 2015 and January 2021, 52 patients with non-gastric SELs (esophagus, n = 15; duodenum, n = 26; colon, n = 11) were enrolled. The ability of EUS-AI to differentiate GISTs from non-GISTs in non-gastric SELs was examined. The accuracy, sensitivity, and specificity of EUS-AI for discriminating GISTs from non-GISTs in non-gastric SELs were 94.4%, 100%, and 86.1%, respectively, with an area under the curve of 0.98 based on the cutoff value set using the Youden index. In the subanalysis, the accuracy, sensitivity, and specificity of EUS-AI were highest in the esophagus (100%, 100%, 100%; duodenum, 96.2%, 100%, 0%; colon, 90.9%, 100%, 0%); the cutoff values were determined using the Youden index or the value determined using stomach cases. The diagnostic accuracy of EUS-AI increased as lesion size increased, regardless of lesion location. EUS-AI based on gastric SELs had good diagnostic ability for non-gastric GISTs.
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