544 citations · 598 across the 8 of their papers we have counts for
8 papers
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…
FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence
Sebastian Antony Joseph, Lily Chen, Jan Trienes +5
Plain language summarization with LLMs can be useful for improving textual accessibility of technical content. But how factual are these summaries in a high-stakes domain like medi…
InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification
Jan Trienes, Sebastian Joseph, Jörg Schlötterer +5
Text simplification aims to make technical texts more accessible to laypeople but often results in deletion of information and vagueness. This work proposes InfoLossQA, a framework…
Guidance in Radiology Report Summarization: An Empirical Evaluation and Error Analysis
Jan Trienes, Paul Youssef, Jörg Schlötterer +1
Automatically summarizing radiology reports into a concise impression can reduce the manual burden of clinicians and improve the consistency of reporting. Previous work aimed to en…
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
Meike Nauta, Jan Trienes, Shreyasi Pathak +6
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing black boxes raised the question of how to evaluate explanations of machine learning…
Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical Records
Jan Trienes, Dolf Trieschnigg, Christin Seifert +1
Unstructured information in electronic health records provide an invaluable resource for medical research. To protect the confidentiality of patients and to conform to privacy regu…