5 citations · 7 across the 5 of their papers we have counts for
5 papers
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
Lisa Raithel, Hui-Syuan Yeh, Shuntaro Yada +11
User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world. However,…
Factuality Detection using Machine Translation -- a Use Case for German Clinical Text
Mohammed Bin Sumait, Aleksandra Gabryszak, Leonhard Hennig +1
Factuality can play an important role when automatically processing clinical text, as it makes a difference if particular symptoms are explicitly not present, possibly present, not…
Which anonymization technique is best for which NLP task? -- It depends. A Systematic Study on Clinical Text Processing
Iyadh Ben Cheikh Larbi, Aljoscha Burchardt, Roland Roller
Clinical text processing has gained more and more attention in recent years. The access to sensitive patient data, on the other hand, is still a big challenge, as text cannot be sh…
A Medical Information Extraction Workbench to Process German Clinical Text
Roland Roller, Laura Seiffe, Ammer Ayach +9
Background: In the information extraction and natural language processing domain, accessible datasets are crucial to reproduce and compare results. Publicly available implementatio…
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient's Perspective
Lisa Raithel, Philippe Thomas, Roland Roller +3
In this work, we present the first corpus for German Adverse Drug Reaction (ADR) detection in patient-generated content. The data consists of 4,169 binary annotated documents from…