Omar S. M. El Nahhas

14 papers Journal 10Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Abnormality-Driven Representation Learning for Radiology Imaging. MICCAI (4) Marta Ligero, Tim Lenz, Georg Wölflein, Omar S. M. El Nahhas, Daniel Truhn, Jakob Nikolas Kather
2025	—	`conf`	Diagnosis with Nanoscale Protein Distributions: Single-Molecule Fluorescence Localization Microscopy and Attention-Based Learning. ISBI 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
2024	—	`conf`	A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification. ECCV Workshops (16) 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
2024	J	`jnl`	Abnormality-Driven Representation Learning for Radiology Imaging. CoRR Marta Ligero, Tim Lenz, Georg Wölflein, Omar S. M. El Nahhas, Daniel Truhn, Jakob Nikolas Kather
2024	J	`jnl`	Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology. CoRR 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
2024	J	`jnl`	Benchmarking foundation models as feature extractors for weakly-supervised computational pathology. CoRR 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
2024	J	`jnl`	Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization. CoRR Firas Khader, Omar S. M. El Nahhas, Tianyu Han, Gustav Müller-Franzes, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn
2024	J	`jnl`	In-context learning enables multimodal large language models to classify cancer pathology images. CoRR 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
2024	—	`conf`	Joint Multi-task Learning Improves Weakly-Supervised Biomarker Prediction in Computational Pathology. MICCAI (4) Omar S. M. El Nahhas, Georg Wölflein, Marta Ligero, Tim Lenz, Marko van Treeck, Firas Khader, Daniel Truhn, Jakob Nikolas Kather
2024	J	`jnl`	Joint multi-task learning improves weakly-supervised biomarker prediction in computational pathology. CoRR Omar S. M. El Nahhas, Georg Wölflein, Marta Ligero, Tim Lenz, Marko van Treeck, Firas Khader, Daniel Truhn, Jakob Nikolas Kather
2024	J	`jnl`	Reducing self-supervised learning complexity improves weakly-supervised classification performance in computational pathology. CoRR Tim Lenz, Omar S. M. El Nahhas, Marta Ligero, Jakob Nikolas Kather
2023	J	`jnl`	A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology. CoRR 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
2023	J	`jnl`	From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology. CoRR 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
2023	J	`jnl`	Regression-based Deep-Learning predicts molecular biomarkers from pathology slides. CoRR 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