New network topology approaches reveal differential correlation patterns in breast cancer. - Michael Bockmayr; Frederick Klauschen; Balazs Györffy; Carsten Denkert; Jan Budczies (BMC Syst. Biol., 2013)

Semiconductor sequencing: how many flows do you need? - Jan Budczies; Michael Bockmayr; Denise Treue; Frederick Klauschen; Carsten Denkert (Bioinform., 2015)

Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles. - Alexander Binder; Michael Bockmayr; Miriam Hägele; Stephan Wienert; Daniel Heim; Katharina Hellweg; Albrecht Stenzinger; Laura Parlow; Jan Budczies; Benjamin Goeppert; Denise Treue; Manato Kotani; et al. (CoRR, 2018)

Resolving challenges in deep learning-based analyses of histopathological images using explanation methods. - Miriam Hägele; Philipp Seegerer; Sebastian Lapuschkin; Michael Bockmayr; Wojciech Samek; Frederick Klauschen; Klaus-Robert Müller; Alexander Binder (CoRR, 2019)

Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images. - Philipp Seegerer; Alexander Binder; René Saitenmacher; Michael Bockmayr; Maximilian Alber; Philipp Jurmeister; Frederick Klauschen; Klaus-Robert Müller (AI and ML for Digital Pathology, 2020)

Explaining Bayesian Neural Networks. - Kirill Bykov; Marina M.-C. Höhne; Adelaida Creosteanu; Klaus-Robert Müller; Frederick Klauschen; Shinichi Nakajima; Marius Kloft (CoRR, 2021)

Morphological and molecular breast cancer profiling through explainable machine learning. - Alexander Binder; Michael Bockmayr; Miriam Hägele; Stephan Wienert; Daniel Heim; Katharina Hellweg; Masaru Ishii; Albrecht Stenzinger; Andreas Hocke; Carsten Denkert; Klaus-Robert Müller; Frederick Klauschen (Nat. Mach. Intell., 2021)

DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology. - Marco Aversa; Gabriel Nobis; Miriam Hägele; Kai Standvoss; Mihaela Chirica; Roderick Murray-Smith; Ahmed M. Alaa; Lukas Ruff; Daniela Ivanova; Wojciech Samek; Frederick Klauschen; Bruno Sanguinetti; et al. (NeurIPS, 2023)

Leveraging weak complementary labels to improve semantic segmentation of hepatocellular carcinoma and cholangiocarcinoma in H&E-stained slides. - Miriam Hägele; Johannes Eschrich; Lukas Ruff; Maximilian Alber; Simon Schallenberg; Adrien Guillot; Christoph Roderburg; Frank Tacke; Frederick Klauschen (CoRR, 2023)

Creation of a structured molecular genomics report for Germany as a local adaption of HL7's Genomic Reporting Implementation Guide. - Caroline Stellmach; Julian Sass; Bernd Auber; Martin Boeker; Thomas F. Wienker; Andrew J. Heidel; Manuela Benary; Simon Schumacher; Stephan Ossowski; Frederick Klauschen; Yvonne Möller; Rita Schmutzler; et al. (J. Am. Medical Informatics Assoc., 2023)

xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology. - Julius Hense; Mina Jamshidi Idaji; Oliver Eberle; Thomas Schnake; Jonas Dippel; Laure Ciernik; Oliver Buchstab; Andreas Mock; Frederick Klauschen; Klaus-Robert Müller (NeurIPS, 2024)

RudolfV: A Foundation Model by Pathologists for Pathologists. - Jonas Dippel; Barbara Feulner; Tobias Winterhoff; Simon Schallenberg; Gabriel Dernbach; Andreas Kunft; Stephan Tietz; Philipp Jurmeister; David Horst; Lukas Ruff; Klaus-Robert Müller; Frederick Klauschen; et al. (CoRR, 2024)

AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics. - Jonas Dippel; Niklas Prenißl; Julius Hense; Philipp Liznerski; Tobias Winterhoff; Simon Schallenberg; Marius Kloft; Oliver Buchstab; David Horst; Maximilian Alber; Lukas Ruff; Klaus-Robert Müller; et al. (CoRR, 2024)

xCG: Explainable Cell Graphs for Survival Prediction in Non-Small Cell Lung Cancer. - Marvin Sextro; Gabriel Dernbach; Kai Standvoss; Simon Schallenberg; Frederick Klauschen; Klaus-Robert Müller; Maximilian Alber; Lukas Ruff (CoRR, 2024)

Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics. - Maximilian Alber; Stephan Tietz; Jonas Dippel; Timo Milbich; Timothée Lesort; Panos Korfiatis; Moritz Krügener; Beatriz Perez Cancer; Neelay Shah; Alexander Möllers; Philipp Seegerer; Alexandra Carpen-Amarie; et al. (CoRR, 2025)

MeDi: Metadata-Guided Diffusion Models for Mitigating Biases in Tumor Classification. - David Jacob Drexlin; Jonas Dippel; Julius Hense; Niklas Prenißl; Grégoire Montavon; Frederick Klauschen; Klaus-Robert Müller (CoRR, 2025)

Towards Robust Foundation Models for Digital Pathology. - Jonah Kömen; Edwin D. de Jong; Julius Hense; Hannah Marienwald; Jonas Dippel; Philip Naumann; Eric Marcus; Lukas Ruff; Maximilian Alber; Jonas Teuwen; Frederick Klauschen; Klaus-Robert Müller (CoRR, 2025)