Frederick Klauschen

According to our database, Frederick Klauschen authored at least 17 papers between 2013 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, July, 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, June, 2025

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, Kai Standvoss, Gabriel Dernbach, Edwin D. de Jong, Simon Schallenberg, Andreas Kunft, Helmut Hoffer von Ankershoffen, Gavin Schaeferle, Patrick Duffy, Matt Redlon, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Andrew P. Norgan

CoRR, January, 2025

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

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, Frederick Klauschen

CoRR, 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, Maximilian Alber

CoRR, 2024

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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

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, Arsenij Ustjanzew, Patrick Werner, Aurelie Tomczak, Thimo Hölter, Sylvia Thun

J. Am. Medical Informatics Assoc., 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

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, Luis Oala

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Explaining Bayesian Neural Networks.

Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft

CoRR, 2021

2020

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

2019

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

2018

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, Masaru Ishii, Manfred Dietel, Andreas Hocke, Carsten Denkert, Klaus-Robert Müller, Frederick Klauschen

CoRR, 2018

2015

Semiconductor sequencing: how many flows do you need?

Jan Budczies, Michael Bockmayr, Denise Treue, Frederick Klauschen, Carsten Denkert

Bioinform., 2015

2013

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