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Real-time computer-aided diagnosis of focal pancreatic masses from endoscopic ultrasound imaging based on a hybrid convolutional and long short-term memory neural network model.

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Title: Real-time computer-aided diagnosis of focal pancreatic masses from endoscopic ultrasound imaging based on a hybrid convolutional and long short-term memory neural network model.
Authors: Udriștoiu AL; Faculty of Automation, Computers and Electronics, University of Craiova, Craiova, Romania., Cazacu IM; Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Craiova, Romania., Gruionu LG; Faculty of Mechanics, University of Craiova, Craiova, Romania., Gruionu G; Faculty of Mechanics, University of Craiova, Craiova, Romania.; Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, United States of America., Iacob AV; Faculty of Automation, Computers and Electronics, University of Craiova, Craiova, Romania., Burtea DE; Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Craiova, Romania., Ungureanu BS; Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Craiova, Romania., Costache MI; Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Craiova, Romania., Constantin A; Gastroenterology Department, Ponderas Academic Hospital, Bucharest, Romania., Popescu CF; Pathology Department, Emergency County Clinical Hospital Craiova, Craiova, Romania., Udriștoiu Ș; Faculty of Automation, Computers and Electronics, University of Craiova, Craiova, Romania.; INNES Worldwide LLC, Craiova, Romania., Săftoiu A; Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Craiova, Romania.; Gastroenterology Department, Ponderas Academic Hospital, Bucharest, Romania.
Source: PloS one [PLoS One] 2021 Jun 28; Vol. 16 (6), pp. e0251701. Date of Electronic Publication: 2021 Jun 28 (Print Publication: 2021).
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1932-6203
DOI:10.1371/journal.pone.0251701