109 citations · 175 across the 5 of their papers we have counts for
5 papers · 1 filter
CliniBench: A Clinical Outcome Prediction Benchmark for Generative and Encoder-Based Language Models
Paul Grundmann, Dennis Fast, Jan Frick +4
With their growing capabilities, generative large language models (LLMs) are being increasingly investigated for complex medical tasks. However, their effectiveness in real-world c…
MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data
Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou +6
As large language models (LLMs) like OpenAI's GPT series continue to make strides, we witness the emergence of artificial intelligence applications in an ever-expanding range of fi…
MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain
Keno K. Bressem, Jens-Michalis Papaioannou, Paul Grundmann +12
This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million Germ…
Cross-Lingual Knowledge Transfer for Clinical Phenotyping
Jens-Michalis Papaioannou, Paul Grundmann, Betty van Aken +5
Clinical phenotyping enables the automatic extraction of clinical conditions from patient records, which can be beneficial to doctors and clinics worldwide. However, current state-…
Learning Contextualized Document Representations for Healthcare Answer Retrieval
Sebastian Arnold, Betty van Aken, Paul Grundmann +2
We present Contextual Discourse Vectors (CDV), a distributed document representation for efficient answer retrieval from long healthcare documents. Our approach is based on structu…