4 citations · 4 across the 4 of their papers we have counts for
4 papers
Arbitrary Data as Images: Fusion of Patient Data Across Modalities and Irregular Intervals with Vision Transformers
Malte Tölle, Mohamad Scharaf, Samantha Fischer +7
A patient undergoes multiple examinations in each hospital stay, where each provides different facets of the health status. These assessments include temporal data with varying sam…
Multi-Modal Dataset Creation for Federated Learning with DICOM Structured Reports
Malte Tölle, Lukas Burger, Halvar Kelm +21
Purpose: Federated training is often hindered by heterogeneous datasets due to divergent data storage options, inconsistent naming schemes, varied annotation procedures, and dispar…
FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels
Malte Tölle, Fernando Navarro, Sebastian Eble +3
Federated learning is one popular paradigm to train a joint model in a distributed, privacy-preserving environment. But partial annotations pose an obstacle meaning that categories…
Real World Federated Learning with a Knowledge Distilled Transformer for Cardiac CT Imaging
Malte Tölle, Philipp Garthe, Clemens Scherer +22
Federated learning is a renowned technique for utilizing decentralized data while preserving privacy. However, real-world applications often face challenges like partially labeled…