Direct prediction of genetic aberrations from pathology images in gastric cancer with swarm learning

BACKGROUND: Computational pathology uses deep learning (DL) to extract biomarkers from routine pathology slides. Large multicentric datasets improve performance, but such datasets are scarce for gastric cancer. This limitation could be overcome by Swarm Learning (SL). METHODS: Here, we report the re...

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Detalles Bibliográficos
Autores principales: Saldanha, Oliver Lester, Muti, Hannah Sophie, Grabsch, Heike I., Langer, Rupert, Dislich, Bastian, Kohlruss, Meike, Keller, Gisela, van Treeck, Marko, Hewitt, Katherine Jane, Kolbinger, Fiona R., Veldhuizen, Gregory Patrick, Boor, Peter, Foersch, Sebastian, Truhn, Daniel, Kather, Jakob Nikolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9950158/
https://www.ncbi.nlm.nih.gov/pubmed/36264524
http://dx.doi.org/10.1007/s10120-022-01347-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9950158/
https://www.ncbi.nlm.nih.gov/pubmed/36264524
http://dx.doi.org/10.1007/s10120-022-01347-0

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