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ORCIDJakob Nikolas Kather
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2020 – today
- 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 - [i16]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) - [i15]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) - [i14]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) - [i13]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) - [i12]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) - [i11]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) - [i10]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) - [i9]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) - [i8]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) - [i7]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) - 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 L. Ghaffari, 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 2023-11-25 16:00 CET by the dblp team
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