M. C. Maurer

Predicting Cognitive Impairment from Polysomnography using Graph Neural Networks

FFM-CP: Cross-Backbone Fusion of Vision-Language Foundation Models for Few-Shot Computational Pathology

It is suggested that combining complementary pretrained representations can improve histopathological classification when annotations are limited, and FFM-CP achieves higher mean macro-F1 than the strongest individually adapted member of each fused set in 50 of 54 comparisons.

Evaluating Graph Neural Network Architectures for Multi-Omics Cancer Subtyping using Methylation and Gene Expression Profiles

A benchmarking study on multiple GNNs on a Protein-Protein Interaction (PPI) network for Kidney Renal Clear Cell Carcinoma and Breast cancer subtype prediction, performing an in-depth investigation of architectures, incorporating skip connections and various data modalities.