A deep learning model to detect pancreatic ductal adenocarcinoma on endoscopic ultrasound-guided fin...
A deep learning model to detect pancreatic ductal adenocarcinoma on endoscopic ultrasound-guided fine-needle biopsy
About this item
Full title
Author / Creator
Naito, Yoshiki , Tsuneki, Masayuki , Fukushima, Noriyoshi , Koga, Yutaka , Higashi, Michiyo , Notohara, Kenji , Aishima, Shinichi , Ohike, Nobuyuki , Tajiri, Takuma , Yamaguchi, Hiroshi , Fukumura, Yuki , Kojima, Motohiro , Hirabayashi, Kenichi , Hamada, Yoshihiro , Norose, Tomoko , Kai, Keita , Omori, Yuko , Sukeda, Aoi , Noguchi, Hirotsugu , Uchino, Kaori , Itakura, Junya , Okabe, Yoshinobu , Yamada, Yuichi , Akiba, Jun , Kanavati, Fahdi , Oda, Yoshinao , Furukawa, Toru and Yano, Hirohisa
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
Histopathological diagnosis of pancreatic ductal adenocarcinoma (PDAC) on endoscopic ultrasonography-guided fine-needle biopsy (EUS-FNB) specimens has become the mainstay of preoperative pathological diagnosis. However, on EUS-FNB specimens, accurate histopathological evaluation is difficult due to low specimen volume with isolated cancer cells and...
Alternative Titles
Full title
A deep learning model to detect pancreatic ductal adenocarcinoma on endoscopic ultrasound-guided fine-needle biopsy
Authors, Artists and Contributors
Author / Creator
Tsuneki, Masayuki
Fukushima, Noriyoshi
Koga, Yutaka
Higashi, Michiyo
Notohara, Kenji
Aishima, Shinichi
Ohike, Nobuyuki
Tajiri, Takuma
Yamaguchi, Hiroshi
Fukumura, Yuki
Kojima, Motohiro
Hirabayashi, Kenichi
Hamada, Yoshihiro
Norose, Tomoko
Kai, Keita
Omori, Yuko
Sukeda, Aoi
Noguchi, Hirotsugu
Uchino, Kaori
Itakura, Junya
Okabe, Yoshinobu
Yamada, Yuichi
Akiba, Jun
Kanavati, Fahdi
Oda, Yoshinao
Furukawa, Toru
Yano, Hirohisa
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_8efa37602ae04180b4b65201336e8c57
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8efa37602ae04180b4b65201336e8c57
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-021-87748-0
