Georg Wölflein

According to our database, Georg Wölflein authored at least 14 papers between 2021 and 2025.

Collaborative distances:

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

2025

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning.

Tim Lenz, Peter Neidlinger, Marta Ligero, Georg Wölflein, Marko van Treeck, Jakob Nikolas Kather

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

LLM Agents Making Agent Tools.

Georg Wölflein, Dyke Ferber, Daniel Truhn, Ognjen Arandjelovic, Jakob Nikolas Kather

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Abnormality-Driven Representation Learning for Radiology Imaging.

Marta Ligero, Tim Lenz, Georg Wölflein, Omar S. M. El Nahhas, Daniel Truhn, Jakob Nikolas Kather

CoRR, 2024

End-To-End Clinical Trial Matching with Large Language Models.

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

CoRR, 2024

Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology.

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

CoRR, 2024

In-context learning enables multimodal large language models to classify cancer pathology images.

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

CoRR, 2024

Joint Multi-task Learning Improves Weakly-Supervised Biomarker Prediction in Computational Pathology.

Omar S. M. El Nahhas, Georg Wölflein, Marta Ligero, Tim Lenz, Marko van Treeck, Firas Khader, Daniel Truhn, Jakob Nikolas Kather

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification.

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

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2023

Whole-Slide Images and Patches of Clear Cell Renal Cell Carcinoma Tissue Sections Counterstained with Hoechst 33342, CD3, and CD8 Using Multiple Immunofluorescence.

Georg Wölflein, In Hwa Um, David J. Harrison, Ognjen Arandjelovic

Data, February, 2023

From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology.

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

CoRR, 2023

A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology.

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

CoRR, 2023

Deep Multiple Instance Learning with Distance-Aware Self-Attention.

Georg Wölflein, Lucie Charlotte Magister, Pietro Liò, David J. Harrison, Ognjen Arandjelovic

CoRR, 2023

HoechstGAN: Virtual Lymphocyte Staining Using Generative Adversarial Networks.

Georg Wölflein, In Hwa Um, David J. Harrison, Ognjen Arandjelovic

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

2021

Determining Chess Game State from an Image.

Georg Wölflein, Ognjen Arandjelovic

J. Imaging, 2021