13 citations · 14 across the 2 of their papers we have counts for
3 papers · 1 filter
In-context learning enables multimodal large language models to classify cancer pathology images
Dyke Ferber, Georg Wölflein, Isabella C. Wiest +8
Medical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models. However, this proce…
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 +9
Hematoxylin- and eosin (H&E) stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. In recent years, development of deep learning-based methods in computation…
Regression-based Deep-Learning predicts molecular biomarkers from pathology slides
Omar S. M. El Nahhas, Chiara M. L. Loeffler, Zunamys I. Carrero +14
Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical la…