Search Results for author:
Found 17 papers, 7 papers with code
Findings of the WMT 2020 Biomedical Translation Shared Task: Basque, Italian and Russian as New Additional Languages
Machine translation of scientific abstracts and terminologies has the potential to support health professionals and biomedical researchers in some of their activities.
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient’s Perspective
In this work, we present the first corpus for German Adverse Drug Reaction (ADR) detection in patient-generated content.
Findings of the WMT 2021 Biomedical Translation Shared Task: Summaries of Animal Experiments as New Test Set
In the sixth edition of the WMT Biomedical Task, we addressed a total of eight language pairs, namely English/German, English/French, English/Spanish, English/Portuguese, English/Chinese, English/Russian, English/Italian, and English/Basque.
Subjective Text Complexity Assessment for German
In order to provide suitable text for the target audience, it is necessary to measure its complexity.
An Annotated Corpus of Textual Explanations for Clinical Decision Support
In recent years, machine learning for clinical decision support has gained more and more attention.
Explainable Artificial Intelligence (XAI)
Feature Importance
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world.
xMEN: A Modular Toolkit for Cross-Lingual Medical Entity Normalization
Weakly supervised cross-encoders are effective when no training data is available for the target task.
Factuality Detection using Machine Translation -- a Use Case for German Clinical Text
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 mentioned, or affirmed.
Which anonymization technique is best for which NLP task? -- It depends. A Systematic Study on Clinical Text Processing
Clinical text processing has gained more and more attention in recent years.
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient's Perspective
In this work, we present the first corpus for German Adverse Drug Reaction (ADR) detection in patient-generated content.
A Medical Information Extraction Workbench to Process German Clinical Text
However, in the context of clinical text processing the number of accessible datasets is scarce -- and so is the number of existing tools.
When Performance is not Enough -- A Multidisciplinary View on Clinical Decision Support
Scientific publications about machine learning in healthcare are often about implementing novel methods and boosting the performance - at least from a computer science perspective.
From Witch's Shot to Music Making Bones -- Resources for Medical Laymen to Technical Language and Vice Versa
This also applies to information about a person's health status.
SIA: A Scalable Interoperable Annotation Server for Biomedical Named Entities
Recent years showed a strong increase in biomedical sciences and an inherent increase in publication volume.
Cross-lingual Candidate Search for Biomedical Concept Normalization
Biomedical concept normalization links concept mentions in texts to a semantically equivalent concept in a biomedical knowledge base.
Creation of an Annotated Corpus of Spanish Radiology Reports
This paper presents a new annotated corpus of 513 anonymized radiology reports written in Spanish.
Improving distant supervision using inference learning
Distant supervision is a widely applied approach to automatic training of relation extraction systems and has the advantage that it can generate large amounts of labelled data with minimal effort.
