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ORCIDDaniel Truhn
- > Home > Persons > Daniel Truhn
Publications
- 2025
[c26]Georg Wölflein
, Dyke Ferber, Daniel Truhn, Ognjen Arandjelovic, Jakob Nikolas Kather:
LLM Agents Making Agent Tools. ACL (1) 2025: 26092-26130- [c24]Marta Ligero, Tim Lenz, Georg Wölflein, Omar S. M. El Nahhas, Daniel Truhn, Jakob Nikolas Kather:
Abnormality-Driven Representation Learning for Radiology Imaging. MICCAI (4) 2025: 14-24 - [i56]Georg Wölflein, Dyke Ferber, Daniel Truhn, Ognjen Arandjelovic, Jakob Nikolas Kather:
LLM Agents Making Agent Tools. CoRR abs/2502.11705 (2025) - 2024
- [c23]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 Pathology Slide Classification. ECCV Workshops (16) 2024: 68-87 - [c21]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. MICCAI (4) 2024: 254-262 - [i41]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) - [i40]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) - [i39]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) - [i35]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) - [i28]Marta Ligero, Tim Lenz, Georg Wölflein, Omar S. M. El Nahhas, Daniel Truhn, Jakob Nikolas Kather:
Abnormality-Driven Representation Learning for Radiology Imaging. CoRR abs/2411.16803 (2024) - 2023
- [i13]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) - [i11]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)
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