S. Lenz et al. (Mainz): An Open Benchmark for Assessing Large Language Models for German Tumor Documentation

F. Marton Csaszar et al. (Dresden): LLM-based document classification and parameter extraction pipeline for efficient information exchange in the German healthcare

P. Richter-Pechanski et al. (Heidelberg): Medication information extraction using local large language models

R. Noll et al. (Frankfurt): Enhancing Large Language Models for Structured Medical Documentation in German Healthcare

J. Schweer (Heidelberg): Current consent approaches to secondary research with patient data: Ethical challenges and outlook

E. Prochaska (Dresden): ICFx-WebApp als Anwendung zur Erfassung von Teilhabestörungen auf ICF-Basis

M. Jafarpour (Vienna): Integrating Patient-Reported Outcomes with FHIR: A Scalable and FAIR-Compliant Solution for EAV-Based Systems

M. Wolfien (Dresden): Enhancing Molecular Tumor Boards with User-Centered Visualizations - Embedding PROMs in cBioPortal

T. Kulvicius (Heidelberg): Multi-sensor approach for infant movement classification

ePoster

• N. Freise et al. (Heilbronn and Heidelberg): IPROPS- Iterative Prompt Refinement for Optimizing Privacy-Preserving Synthetic Data Generation
• M. Haghi et al. (Heidelberg): LSTM-based Emotion Recognition: A Comparative Study of Single-Signal and Multi-Sensor Fusion Approaches
• AC. Hauschild et al. (Göttingen): Evaluating Transformer Models for ICD Code Embeddings in Predicting Clinical Outcomes
• M. Hübner et al. (Berlin): Federated documentation and data use within NUM and EU project Screen4Care
• L. Jahn et al. (Göttingen): Benchmarking methods for 2D infant pose estimation
• M. Schiltenwolf (Berlin): Large Language Models in Mental Health Diagnostics: Performance Assessment in Symptom Identification and Interview Section Extraction
• C. Schneider, B. Trukeschitz et al. (Wiener Neustadt): “Now, I understand!”: Digital support in 24-hour care – learnings from co-creating and friendly user testing
• M. Seiferling et al. (Heidelberg): Unlocking German Clinical Text Data: Advanced De-Identification for LLM Training