44 PROSPECTIVE COMPARISON STUDY OF EUS-FNA ONSITE CYTOLOGY DIAGNOSIS BY PATHOLOGIST VERSUS OUR DESIGNED DEEP LEARNING ALGORHYTHM IN SUSPECTED PANCREATIC CANCER
Author:
Publisher
Elsevier BV
Subject
Gastroenterology,Hepatology
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. SI-ViT: Shuffle instance-based Vision Transformer for pancreatic cancer ROSE image classification;Computer Methods and Programs in Biomedicine;2024-02
2. Artificial Intelligence in Endoscopic Ultrasonography-Guided Fine-Needle Aspiration/Biopsy (EUS-FNA/B) for Solid Pancreatic Lesions: Opportunities and Challenges;Diagnostics;2023-09-26
3. MSHT: Multi-Stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer;IEEE Journal of Biomedical and Health Informatics;2023-04
4. A deep learning-based segmentation system for rapid onsite cytologic pathology evaluation of pancreatic masses: A retrospective, multicenter, diagnostic study;eBioMedicine;2022-06
5. A Deep Learning-Based Segmentation System for Rapid Onsite Cytologic Pathology Evaluation of Pancreatic Masses: A Retrospective, Multicenter, Diagnostic Study;SSRN Electronic Journal;2022
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