Volkmar Schulz

This paper evaluates adversarial robustness of CNNs and ViTs in computational pathology, finding ViTs are more robust to attacks.

This study benchmarks AI methods for end-to-end computational pathology, showing ResNet and ViT outperform MIL and CLAM in mutation prediction but not in tumor subtyping.

This paper introduces a method to generate high-resolution artificial radiographs using generative models to overcome data sharing barriers in medicine.