We exhibit at CeBIT at the BMWi booth

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Natural Language Processing

Investigating Natural Language Inference Capabilities of Large Language Modes in Biomedical Claim Verification 

Left: Examples from HealthVer [1]; Right: Example of a claim that is supported and refuted by different evidence [2]  With the rapid growth of biomedical research and the concurrent rise in misinformation, ensuring the accuracy Read more…

Natural Language Processing

Optimizing Relation Extraction in Medical Texts through Active Learning: A Comparative Analysis of Trade-offs

Example from n2c2 of relation extraction [1]  This work explores the effectiveness of employing Clinical BERT for Relation Extraction (RE) tasks in medical texts within an Active Learning (AL) framework. Our main objective is to Read more…

Natural Language Processing

Building A German Clinical Named Entity Recognition System without In-domain Training Data 

Clinical Named Entity Recognition (NER) is essential for extracting important medical insights from clinical narratives. Given the challenges in obtaining expert training datasets for real-world clinical applications related to data protection regulations and the lack Read more…