GGPONC 2.0 - The German Clinical Guideline Corpus for Oncology: Curation Workflow, Annotation Policy, Baseline NER Taggers

1 code implementation • LREC 2022 • Florian Borchert, Christina Lohr, Luise Modersohn, Jonas Witt, Thomas Langer, Markus Follmann, Matthias Gietzelt, Bert Arnrich, Udo Hahn, Matthieu-P. Schapranow

Despite remarkable advances in the development of language resources over the recent years, there is still a shortage of annotated, publicly available corpora covering (German) medical language.

named-entity-recognition Named Entity Recognition +1

German Text Embedding Clustering Benchmark

2 code implementations • 5 Jan 2024 • Silvan Wehrli, Bert Arnrich, Christopher Irrgang

This work introduces a benchmark assessing the performance of clustering German text embeddings in different domains.

Clustering

xMEN: A Modular Toolkit for Cross-Lingual Medical Entity Normalization

1 code implementation • 17 Oct 2023 • Florian Borchert, Ignacio Llorca, Roland Roller, Bert Arnrich, Matthieu-P. Schapranow

Weakly supervised cross-encoders are effective when no training data is available for the target task.

A Real-time Human Pose Estimation Approach for Optimal Sensor Placement in Sensor-based Human Activity Recognition

no code implementations • 6 Jul 2023 • Orhan Konak, Alexander Wischmann, Robin van de Water, Bert Arnrich

This research significantly advances the field of Human Activity Recognition by providing a lightweight, on-device solution for determining the optimal sensor placement, thereby enhancing data anonymization and supporting a multimodal classification approach.

Human Activity Recognition Pose Estimation

Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML

4 code implementations • 8 Jun 2023 • Robin van de Water, Hendrik Schmidt, Paul Elbers, Patrick Thoral, Bert Arnrich, Patrick Rockenschaub

Datasets and code are not always published, and cohort definitions, preprocessing pipelines, and training setups are difficult to reproduce.

Benchmarking Kidney Function

DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder

1 code implementation • 21 Nov 2022 • Bjarne Pfitzner, Bert Arnrich

Federated learning (FL) is getting increased attention for processing sensitive, distributed datasets common to domains such as healthcare.

Federated Learning Synthetic Data Generation

Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Data

2 code implementations • 6 May 2022 • Joceline Ziegler, Bjarne Pfitzner, Heinrich Schulz, Axel Saalbach, Bert Arnrich

We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients.

Binary Classification Federated Learning +1

Implicit Model Specialization through DAG-based Decentralized Federated Learning

1 code implementation • 1 Nov 2021 • Jossekin Beilharz, Bjarne Pfitzner, Robert Schmid, Paul Geppert, Bert Arnrich, Andreas Polze

Federated learning allows a group of distributed clients to train a common machine learning model on private data.

Federated Learning