Marko van Treeck

According to our database, Marko van Treeck authored at least 7 papers between 2023 and 2025.

Collaborative distances:

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

2025

Diagnosis with Nanoscale Protein Distributions: Single-Molecule Fluorescence Localization Microscopy and Attention-Based Learning.

Alistair Curd, Hayley Slaney, Scarlet F. Brockmöller, Andras-Gabor Miklosi, Deep Arora, Andrew Lewington, James H. Felce, Omar S. M. El Nahhas, Marko van Treeck, Jakob Nikolas Kather, Phil Quirke

Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 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

2024

Privacy-preserving large language models for structured medical information retrieval.

Isabella C. Wiest, Dyke Ferber, Jiefu Zhu, Marko van Treeck, Sonja K. Meyer, Radhika Juglan, Zunamys I. Carrero, Daniel Paech, Jens Kleesiek, Matthias P. Ebert, Daniel Truhn, Jakob Nikolas Kather

npj Digit. Medicine, 2024

Benchmarking foundation models as feature extractors for weakly-supervised computational pathology.

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

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

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

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

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

CoRR, 2023