Publications

Michael Rade, Markus Kreuz, Angelika Borkowetz, Ulrich Sommer, Conny Blumert, Susanne Füssel, Catharina Bertram, Dennis Löffler, Dominik J. Otto, Livia A. Wöller, Carolin Schimmelpfennig, Ulrike Köhl, Ann-Cathrin Gottschling, Pia Hönscheid, Gustavo B. Baretton, Manfred Wirth, Christian Thomas, Friedemann Horn, and Kristin Reiche. A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer. Molecular Medicine, (30)1Springer Science and Business Media LLC, February 2024. [PUMA: biopsies formalin-fixed cancer predictionprostate risk-score transcriptomic applicable paraffin-embedded from:scadsfct] URL

Mika Katalinic, Martin Schenk, Stefan Franke, Alexander Katalinic, Thomas Neumuth, Andreas Dietz, Matthaeus Stoehr, and Jan Gaebel. Generation of a Realistic Synthetic Laryngeal Cancer Cohort for AI Applications. Cancers, (16)3:639, MDPI AG, February 2024. [PUMA: Cancer Realistic Synthetic Applications Cohort AI Laryngeal from:scadsfct Generation] URL

Markus Bauer, Lennart Schneider, Marit Bernhardt, Christoph Augenstein, Glen Kristiansen, and Bogdan Franczyk. An Open-Source Approach for Digital Prostate Cancer Histopathology: Bringing AI into Practice. Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS, 729-738, SciTePress, 2024. [PUMA: Cancer Histopatholog Digital AI Prostate from:scadsfct Open-Source]

Markus Bauer, and Christoph Augenstein. Self-supervised Learning in Histopathology: New Perspectives for Prostate Cancer Grading. Pattern Recognition, 348–360, Springer Nature Switzerland, 2024. [PUMA: Cancer Histopathology Learning Self-supervised Prostate Perspectives from:scadsfct New] URL