Predicting the HER2 status in oesophageal cancer from tissue microarrays using convolutional neural networks

BACKGROUND: Fast and accurate diagnostics are key for personalised medicine. Particularly in cancer, precise diagnosis is a prerequisite for targeted therapies, which can prolong lives. In this work, we focus on the automatic identification of gastroesophageal adenocarcinoma (GEA) patients that qual...

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Detalles Bibliográficos
Autores principales: Pisula, Juan I., Datta, Rabi R., Valdez, Leandra Börner, Avemarg, Jan-Robert, Jung, Jin-On, Plum, Patrick, Löser, Heike, Lohneis, Philipp, Meuschke, Monique, dos Santos, Daniel Pinto, Gebauer, Florian, Quaas, Alexander, Walch, Axel, Bruns, Christiane J., Lawonn, Kai, Popp, Felix C., Bozek, Katarzyna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050393/
https://www.ncbi.nlm.nih.gov/pubmed/36717673
http://dx.doi.org/10.1038/s41416-023-02143-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050393/
https://www.ncbi.nlm.nih.gov/pubmed/36717673
http://dx.doi.org/10.1038/s41416-023-02143-y

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