A deep learning model to detect pancreatic ductal adenocarcinoma on endoscopic ultrasound-guided fine-needle biopsy
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Title
A deep learning model to detect pancreatic ductal adenocarcinoma on endoscopic ultrasound-guided fine-needle biopsy
Authors
Keywords
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Journal
Scientific Reports
Volume 11, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2021-04-19
DOI
10.1038/s41598-021-87748-0
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- Cancer Statistics, 2010
- (2010) A. Jemal et al. CA-A CANCER JOURNAL FOR CLINICIANS
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