A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing

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A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing

Author: Angeloni, Miriam; van Doeveren, Thomas; Lindner, Sebastian; Volland, Patrick; Schmelmer, Jorina; Foersch, Sebastian; Matek, Christian; Stoehr, Robert; Geppert, Carol, I; Heers, Hendrik; Wach, Sven; Taubert, Helge; Sikic, Danijel; Wullich, Bernd; van Leenders, Geert J. L. H.; Zaburdaev, Vasily; Eckstein, Markus; Hartmann, Arndt; Boormans, Joost L.; Ferrazzi, Fulvia; Bahlinger, Veronika
Tübinger Autor(en):
Bahlinger, Veronika
Published in: Journal of Pathology Clinical Research (2024), Bd. 10 (2), Article e12369
Verlagsangabe: Hoboken : Wiley
Language: English
Full text: http://dx.doi.org/10.1002/2056-4538.12369
ISSN: 2056-4538
DDC Classifikation: 610 - Medicine and health
Dokumentart: Article
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