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ORCIDJakob Nikolas Kather
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2020 – today
- 2024
[j10]Jan Moritz Niehues
, Gustav Müller-Franzes, Yoni Schirris, Sophia J. Wagner, Michael Jendrusch, Matthias Kloor, Alexander T. Pearson, Hannah Sophie Muti, Katherine Jane Hewitt, Gregory Patrick Veldhuizen, Laura Zigutyte, Daniel Truhn, Jakob Nikolas Kather:
Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance. Comput. Biol. Medicine 175: 108410 (2024)- [j9]Daniel Truhn, Soroosh Tayebi Arasteh, Oliver Lester Saldanha, Gustav Müller-Franzes, Firas Khader, Philip Quirke, Nicholas P. West, Richard Gray, Gordon G. A. Hutchins, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Alexander Brobeil, Tanwei Yuan, Jenny Chang-Claude, Michael Hoffmeister, Sebastian Foersch, Tianyu Han, Sebastian Keil, Maximilian Schulze-Hagen, Peter Isfort, Philipp Bruners, Georgios Kaissis, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather:
Encrypted federated learning for secure decentralized collaboration in cancer image analysis. Medical Image Anal. 92: 103059 (2024) - [j8]Felix Busch, Jakob Nikolas Kather, Christian Johner, Marina Moser, Daniel Truhn, Lisa C. Adams, Keno K. Bressem:
Navigating the European Union Artificial Intelligence Act for Healthcare. npj Digit. Medicine 7(1) (2024) - [j7]Stephen Gilbert, Jakob Nikolas Kather, Aidan Hogan:
Augmented non-hallucinating large language models as medical information curators. npj Digit. Medicine 7(1) (2024) - [i28]Lisa Adams, Felix Busch, Tianyu Han, Jean-Baptiste Excoffier, Matthieu Ortala, Alexander Löser, Hugo J. W. L. Aerts, Jakob Nikolas Kather, Daniel Truhn, Keno K. Bressem:
LongHealth: A Question Answering Benchmark with Long Clinical Documents. CoRR abs/2401.14490 (2024) - [i27]Omar S. M. El Nahhas, Georg Wölflein, Marta Ligero, Tim Lenz, Marko van Treeck, Firas Khader, Daniel Truhn, Jakob Nikolas Kather:
Joint multi-task learning improves weakly-supervised biomarker prediction in computational pathology. CoRR abs/2403.03891 (2024) - [i26]Tim Lenz, Omar S. M. El Nahhas, Marta Ligero, Jakob Nikolas Kather:
Reducing self-supervised learning complexity improves weakly-supervised classification performance in computational pathology. CoRR abs/2403.04558 (2024) - [i25]Dyke Ferber, Georg Wölflein, Isabella C. Wiest, Marta Ligero, Srividhya Sainath, Narmin Ghaffari Laleh, Omar S. M. El Nahhas, Gustav Müller-Franzes, Dirk Jäger, Daniel Truhn, Jakob Nikolas Kather:
In-context learning enables multimodal large language models to classify cancer pathology images. CoRR abs/2403.07407 (2024) - [i24]Dyke Ferber, Omar S. M. El Nahhas, Georg Wölflein, Isabella C. Wiest, Jan Clusmann, Marie-Elisabeth Leßman, Sebastian Foersch, Jacqueline Lammert, Maximilian Tschochohei, Dirk Jäger, Manuel Salto-Tellez, Nikolaus Schultz, Daniel Truhn, Jakob Nikolas Kather:
Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology. CoRR abs/2404.04667 (2024) - [i23]Firas Khader, Omar S. M. El Nahhas, Tianyu Han, Gustav Müller-Franzes, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization. CoRR abs/2406.01314 (2024) - [i22]Tianyu Han, Sven Nebelung, Firas Khader, Jakob Nikolas Kather, Daniel Truhn:
On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction. CoRR abs/2406.16983 (2024) - [i21]Dyke Ferber, Lars Hilgers, Isabella C. Wiest, Marie-Elisabeth Leßmann, Jan Clusmann, Peter Neidlinger, Jiefu Zhu, Georg Wölflein, Jacqueline Lammert, Maximilian Tschochohei, Heiko Böhme, Dirk Jäger, Mihaela Aldea, Daniel Truhn, Christiane Höper, Jakob Nikolas Kather:
End-To-End Clinical Trial Matching with Large Language Models. CoRR abs/2407.13463 (2024) - [i20]Soroosh Tayebi Arasteh, Mahshad Lotfinia, Keno K. Bressem, Robert Siepmann, Dyke Ferber, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn:
RadioRAG: Factual Large Language Models for Enhanced Diagnostics in Radiology Using Dynamic Retrieval Augmented Generation. CoRR abs/2407.15621 (2024) - [i19]Jan Clusmann, Dyke Ferber, Isabella C. Wiest, Carolin V. Schneider, Titus J. Brinker, Sebastian Foersch, Daniel Truhn, Jakob Nikolas Kather:
Prompt Injection Attacks on Large Language Models in Oncology. CoRR abs/2407.18981 (2024) - [i18]Peter Neidlinger, Omar S. M. El Nahhas, Hannah Sophie Muti, Tim Lenz, Michael Hoffmeister, Hermann Brenner, Marko van Treeck, Rupert Langer, Bastian Dislich, Hans Michael Behrens, Christoph Röcken, Sebastian Foersch, Daniel Truhn, Antonio Marra, Oliver Lester Saldanha, Jakob Nikolas Kather:
Benchmarking foundation models as feature extractors for weakly-supervised computational pathology. CoRR abs/2408.15823 (2024) - 2023
- [j6]Tanwei Yuan, Dominic Edelmann, Ziwen Fan, Elizabeth Alwers, Jakob Nikolas Kather, Hermann Brenner, Michael Hoffmeister:
Machine learning in the identification of prognostic DNA methylation biomarkers among patients with cancer: A systematic review of epigenome-wide studies. Artif. Intell. Medicine 143: 102589 (2023) - [c6]Firas Khader, Gustav Müller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Jakob Nikolas Kather, Johannes Stegmaier, Sven Nebelung, Daniel Truhn:
Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection. ISBI 2023: 1-5 - [c5]Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. MLMI@MICCAI (2) 2023: 417-426 - [i17]Sophia J. Wagner, Daniel Reisenbüchler, Nicholas P. West, Jan Moritz Niehues, Gregory Patrick Veldhuizen, Philip Quirke, Heike Irmgard Grabsch, Piet A. van den Brandt, Gordon G. A. Hutchins, Susan D. Richman, Tanwei Yuan, Rupert Langer, Josien Christina Anna Jenniskens, Kelly Offermans, Wolfram Müller, Richard Gray, Stephen B. Gruber, Joel K. Greenson, Gad Rennert, Joseph D. Bonner, Daniel Schmolze, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Michael Hoffmeister, Daniel Truhn, Julia A. Schnabel, Melanie Boxberg, Tingying Peng, Jakob Nikolas Kather:
Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study. CoRR abs/2301.09617 (2023) - [i16]Omar S. M. El Nahhas, Chiara Maria Lavinia Loeffler, Zunamys I. Carrero, Marko van Treeck, Fiona R. Kolbinger, Katherine Jane Hewitt, Hannah Sophie Muti, Mara Graziani, Qinghe Zeng, Julien Calderaro, Nadina Ortiz-Brüchle, Tanwei Yuan, Michael Hoffmeister, Hermann Brenner, Alexander Brobeil, Jorge S. Reis-Filho, Jakob Nikolas Kather:
Regression-based Deep-Learning predicts molecular biomarkers from pathology slides. CoRR abs/2304.05153 (2023) - [i15]Gustav Müller-Franzes, Fritz Müller-Franzes, Luisa Huck, Vanessa Raaff, Eva Kemmer, Firas Khader, Soroosh Tayebi Arasteh, Teresa Nolte, Jakob Nikolas Kather, Sven Nebelung, Christiane Kuhl, Daniel Truhn:
Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers - A multi-institutional evaluation. CoRR abs/2304.08972 (2023) - [i14]Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. CoRR abs/2305.06963 (2023) - [i13]Achim Hekler, Roman C. Maron, Sarah Haggenmüller, Max Schmitt, Christoph Wies, Jochen S. Utikal, Friedegund Meier, Sarah Hobelsberger, Frank Friedrich Gellrich, Mildred Sergon, Axel Hauschild, Lars E. French, Lucie Heinzerling, Justin G. Schlager, Kamran Ghoreschi, Max Schlaak, Franz J. Hilke, Gabriela Poch, Sören Korsing, Carola Berking, Markus V. Heppt, Michael Erdmann, Sebastian Haferkamp, Konstantin Drexler, Dirk Schadendorf, Wiebke Sondermann, Matthias Goebeler, Bastian Schilling, Jakob Nikolas Kather, Eva Krieghoff-Henning, Titus J. Brinker:
Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study. CoRR abs/2306.02800 (2023) - [i12]Soroosh Tayebi Arasteh, Leo Misera, Jakob Nikolas Kather, Daniel Truhn, Sven Nebelung:
Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images. CoRR abs/2308.07688 (2023) - [i11]Soroosh Tayebi Arasteh, Tianyu Han, Mahshad Lotfinia, Christiane Kuhl, Jakob Nikolas Kather, Daniel Truhn, Sven Nebelung:
Empowering Clinicians and Democratizing Data Science: Large Language Models Automate Machine Learning for Clinical Studies. CoRR abs/2308.14120 (2023) - [i10]Tianyu Han, Sven Nebelung, Firas Khader, Tianci Wang, Gustav Mueller-Franzes, Christiane Kuhl, Sebastian Försch, Jens Kleesiek, Christoph Haarburger, Keno K. Bressem, Jakob Nikolas Kather, Daniel Truhn:
Medical Foundation Models are Susceptible to Targeted Misinformation Attacks. CoRR abs/2309.17007 (2023) - [i9]Tianyu Han, Laura Zigutyte, Luisa Huck, Marc Huppertz, Robert Siepmann, Yossi Gandelsman, Christian Blüthgen, Firas Khader, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining. CoRR abs/2309.17123 (2023) - [i8]Georg Wölflein, Dyke Ferber, Asier Rabasco Meneghetti, Omar S. M. El Nahhas, Daniel Truhn, Zunamys I. Carrero, David J. Harrison, Ognjen Arandjelovic, Jakob Nikolas Kather:
A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology. CoRR abs/2311.11772 (2023) - [i7]Omar S. M. El Nahhas, Marko van Treeck, Georg Wölflein, Michaela Unger, Marta Ligero, Tim Lenz, Sophia J. Wagner, Katherine Jane Hewitt, Firas Khader, Sebastian Foersch, Daniel Truhn, Jakob Nikolas Kather:
From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology. CoRR abs/2312.10944 (2023) - 2022
- [j5]Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Loeffler, Amelie Echle, Oliver Lester Saldanha, Faisal Mahmood, Ming Y. Lu, Christian Trautwein, Rupert Langer, Bastian Dislich, Roman David Bülow, Heike Irmgard Grabsch, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Titus J. Brinker, Firas Khader, Daniel Truhn, Nadine T. Gaisa, Peter Boor, Michael Hoffmeister, Volkmar Schulz, Jakob Nikolas Kather:
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Medical Image Anal. 79: 102474 (2022) - [j4]Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Loeffler, Amelie Echle, Oliver Lester Saldanha, Faisal Mahmood, Ming Y. Lu, Christian Trautwein, Rupert Langer, Bastian Dislich, Roman David Bülow, Heike Irmgard Grabsch, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Titus J. Brinker, Firas Khader, Daniel Truhn, Nadine T. Gaisa, Peter Boor, Michael Hoffmeister, Volkmar Schulz, Jakob Nikolas Kather:
Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474. Medical Image Anal. 82: 102622 (2022) - [j3]Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Sven Nebelung, Daniel Truhn:
Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation. Nat. Mac. Intell. 4(11): 1029-1039 (2022) - [j2]Jakob Nikolas Kather, Narmin Ghaffari Laleh, Sebastian Foersch, Daniel Truhn:
Medical domain knowledge in domain-agnostic generative AI. npj Digit. Medicine 5 (2022) - [j1]Narmin Ghaffari Laleh, Chiara Maria Lavinia Loeffler, Julia Grajek, Katerina Stanková, Alexander T. Pearson, Hannah Sophie Muti, Christian Trautwein, Heiko Enderling, Jan Poleszczuk, Jakob Nikolas Kather:
Classical mathematical models for prediction of response to chemotherapy and immunotherapy. PLoS Comput. Biol. 18(2) (2022) - [c4]Adrian Galdran, Katherine Jane Hewitt, Narmin Ghaffari Laleh, Jakob Nikolas Kather, Gustavo Carneiro, Miguel Ángel González Ballester:
Test Time Transform Prediction for Open Set Histopathological Image Recognition. MICCAI (2) 2022: 263-272 - [i6]Adrian Galdran, Katherine Jane Hewitt, Narmin Ghaffari Laleh, Jakob Nikolas Kather, Gustavo Carneiro, Miguel Ángel González Ballester:
Test Time Transform Prediction for Open Set Histopathological Image Recognition. CoRR abs/2206.10033 (2022) - [i5]Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Christoph Haarburger, Maximilian Schulze-Hagen, Philipp Schad, Sandy Engelhardt, Bettina Baeßler, Sebastian Foersch, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation. CoRR abs/2211.03364 (2022) - [i4]Soroosh Tayebi Arasteh, Peter Isfort, Marwin Saehn, Gustav Mueller-Franzes, Firas Khader, Jakob Nikolas Kather, Christiane Kuhl, Sven Nebelung, Daniel Truhn:
Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels. CoRR abs/2211.13606 (2022) - [i3]Gustav Müller-Franzes, Jan Moritz Niehues, Firas Khader, Soroosh Tayebi Arasteh, Christoph Haarburger, Christiane Kuhl, Tianci Wang, Tianyu Han, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Diffusion Probabilistic Models beat GANs on Medical Images. CoRR abs/2212.07501 (2022) - [i2]Firas Khader, Gustav Mueller-Franzes, Tianci Wang, Tianyu Han, Soroosh Tayebi Arasteh, Christoph Haarburger, Johannes Stegmaier, Keno K. Bressem, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Medical Diagnosis with Large Scale Multimodal Transformers: Leveraging Diverse Data for More Accurate Diagnosis. CoRR abs/2212.09162 (2022) - 2021
- [c3]Narmin Ghaffari Laleh, Amelie Echle, Hannah Sophie Muti, Katherine Jane Hewitt, Volkmar Schulz, Jakob Nikolas Kather:
Deep Learning for interpretable end-to-end survival (E-ESurv) prediction in gastrointestinal cancer histopathology. COMPAY@MICCAI 2021: 81-93 - [i1]Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Volkmar Schulz, Christiane Kuhl, Sven Nebelung, Daniel Truhn:
Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning. CoRR abs/2111.11439 (2021)
2010 – 2019
- 2019
- [c2]Francesco Bianconi, Jakob Nikolas Kather, Constantino Carlos Reyes-Aldasoro:
Evaluation of Colour Pre-processing on Patch-Based Classification of H&E-Stained Images. ECDP 2019: 56-64 - 2017
- [c1]Silvia Cascianelli, Raquel Bello-Cerezo, Francesco Bianconi, Mario Luca Fravolini, Mehdi Belal, Barbara Palumbo, Jakob Nikolas Kather:
Dimensionality Reduction Strategies for CNN-Based Classification of Histopathological Images. IIMSS 2017: 21-30
Coauthor Index
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last updated on 2024-09-30 01:00 CEST by the dblp team
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