activity
20222024
most citedROCOv2: Radiology Objects in COntext Version 2, an Updated Multimodal Image Dataset

55 citations · 67 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2024★ 55 cited

ROCOv2: Radiology Objects in COntext Version 2, an Updated Multimodal Image Dataset

Johannes Rückert, Louise Bloch, Raphael Brüngel +11

Automated medical image analysis systems often require large amounts of training data with high quality labels, which are difficult and time consuming to generate. This paper intro…

cs.CL2024

WisPerMed at "Discharge Me!": Advancing Text Generation in Healthcare with Large Language Models, Dynamic Expert Selection, and Priming Techniques on MIMIC-IV

Hendrik Damm, Tabea M. G. Pakull, Bahadır Eryılmaz +5

This study aims to leverage state of the art language models to automate generating the "Brief Hospital Course" and "Discharge Instructions" sections of Discharge Summaries from th…

cs.CL2024★ 3 cited

Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding

Ahmad Idrissi-Yaghir, Amin Dada, Henning Schäfer +17

Recent advances in natural language processing (NLP) can be largely attributed to the advent of pre-trained language models such as BERT and RoBERTa. While these models demonstrate…

cs.CL2024

WisPerMed at BioLaySumm: Adapting Autoregressive Large Language Models for Lay Summarization of Scientific Articles

Tabea M. G. Pakull, Hendrik Damm, Ahmad Idrissi-Yaghir +3

This paper details the efforts of the WisPerMed team in the BioLaySumm2024 Shared Task on automatic lay summarization in the biomedical domain, aimed at making scientific publicati…

cs.CL2023★ 1 cited

On the Impact of Cross-Domain Data on German Language Models

Amin Dada, Aokun Chen, Cheng Peng +12

Traditionally, large language models have been either trained on general web crawls or domain-specific data. However, recent successes of generative large language models, have she…

cs.CL2022★ 8 cited

Domain Adaptation of Transformer-Based Models using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedback

Ahmad Idrissi-Yaghir, Henning Schäfer, Nadja Bauer +1

Understanding customer feedback is becoming a necessity for companies to identify problems and improve their products and services. Text classification and sentiment analysis can p…