Luise Modersohn

A Lightweight Framework for Medical Named Entity Recognition and Relation Extraction.

INTRODUCTION Clinical text in electronic health records contains valuable information for medical research. Named entity recognition (NER) and relation extraction (RE) are key tasks for structuring this information, but existing deep learning approaches are often computationally expensive. METHODS We develop a lightw...

Developing the German Medical Text Corpus (GeMTeX): Legal Compliance and Semantic Enrichment

Large Language Model-Based Text-to-Cypher Generation for Question-Answering on Biomedical Knowledge Graphs.

Few-shot prompting heavily improves query generation quality and enables effective use of smaller models, supporting the practical deployment of locally hosted LLMs for knowledge graph question answering.