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

• Main Authors: Miriam Angeloni (Author), Thomas vanDoeveren (Author), Sebastian Lindner (Author), Patrick Volland (Author), Jorina Schmelmer (Author), Sebastian Foersch (Author), Christian Matek (Author), Robert Stoehr (Author), Carol I Geppert (Author), Hendrik Heers (Author), Sven Wach (Author), Helge Taubert (Author), Danijel Sikic (Author), Bernd Wullich (Author), Geert JLH vanLeenders (Author), Vasily Zaburdaev (Author), Markus Eckstein (Author), Arndt Hartmann (Author), Joost L Boormans (Author), Fulvia Ferrazzi (Author), Veronika Bahlinger (Author)
• Format: Book
• Published: Wiley, 2024-03-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Abstract Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein‐based subtypes. However, if and...