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Correction: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection

Detalles Bibliográficos
Autores principales: Carrillo-Perez, Francisco, Ortuno, Francisco M., Börjesson, Alejandro, Rojas, Ignacio, Herrera, Luis Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655454/
https://www.ncbi.nlm.nih.gov/pubmed/37978549
http://dx.doi.org/10.1186/s40644-023-00636-w
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author Carrillo-Perez, Francisco
Ortuno, Francisco M.
Börjesson, Alejandro
Rojas, Ignacio
Herrera, Luis Javier
author_facet Carrillo-Perez, Francisco
Ortuno, Francisco M.
Börjesson, Alejandro
Rojas, Ignacio
Herrera, Luis Javier
author_sort Carrillo-Perez, Francisco
collection PubMed
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spelling pubmed-106554542023-11-17 Correction: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection Carrillo-Perez, Francisco Ortuno, Francisco M. Börjesson, Alejandro Rojas, Ignacio Herrera, Luis Javier Cancer Imaging Correction BioMed Central 2023-11-17 /pmc/articles/PMC10655454/ /pubmed/37978549 http://dx.doi.org/10.1186/s40644-023-00636-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Correction
Carrillo-Perez, Francisco
Ortuno, Francisco M.
Börjesson, Alejandro
Rojas, Ignacio
Herrera, Luis Javier
Correction: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection
title Correction: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection
title_full Correction: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection
title_fullStr Correction: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection
title_full_unstemmed Correction: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection
title_short Correction: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection
title_sort correction: performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection
topic Correction
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655454/
https://www.ncbi.nlm.nih.gov/pubmed/37978549
http://dx.doi.org/10.1186/s40644-023-00636-w
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