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- W4386283323 abstract "Endoscopic ultrasound (EUS) has emerged as a widely utilized tool in the diagnosis of digestive diseases. In recent years, the potential of artificial intelligence (AI) in healthcare has been gradually recognized, and its superiority in the field of EUS is becoming apparent. Machine learning (ML) and deep learning (DL) are the two main AI algorithms. This paper aims to outline the applications and prospects of artificial intelligence-assisted endoscopic ultrasound (EUS-AI) in digestive diseases over the past decade. The results demonstrated that EUS-AI has shown superiority or at least equivalence to traditional methods in the diagnosis, prognosis, and quality control of subepithelial lesions, early esophageal cancer, early gastric cancer, and pancreatic diseases including pancreatic cystic lesions, autoimmune pancreatitis, and pancreatic cancer. The implementation of EUS-AI has opened up new avenues for individualized precision medicine and has introduced novel diagnostic and treatment approaches for digestive diseases." @default.
- W4386283323 created "2023-08-31" @default.
- W4386283323 creator A5006311711 @default.
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- W4386283323 date "2023-08-30" @default.
- W4386283323 modified "2023-10-16" @default.
- W4386283323 title "Applications and Prospects of Artificial Intelligence-Assisted Endoscopic Ultrasound in Digestive System Diseases" @default.
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- W4386283323 doi "https://doi.org/10.3390/diagnostics13172815" @default.
- W4386283323 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37685350" @default.
- W4386283323 hasPublicationYear "2023" @default.
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