215 citations · 337 across the 17 of their papers we have counts for
5 papers · 1 filter
Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization
Firas Khader, Omar S. M. El Nahhas, Tianyu Han +4
The Transformer model has been pivotal in advancing fields such as natural language processing, speech recognition, and computer vision. However, a critical limitation of this mode…
An Ordinal Regression Framework for a Deep Learning Based Severity Assessment for Chest Radiographs
Patrick Wienholt, Alexander Hermans, Firas Khader +5
This study investigates the application of ordinal regression methods for categorizing disease severity in chest radiographs. We propose a framework that divides the ordinal regres…
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…
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining
Tianyu Han, Laura Žigutytė, Luisa Huck +9
Detecting misleading patterns in automated diagnostic assistance systems, such as those powered by Artificial Intelligence, is critical to ensuring their reliability, particularly…
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers
Firas Khader, Jakob Nikolas Kather, Tianyu Han +4
Whole-Slide Imaging allows for the capturing and digitization of high-resolution images of histological specimen. An automated analysis of such images using deep learning models is…