Oliver Marten's scientific contributions

Publications (4)

Preprint
Full-text available
Background: In the information extraction and natural language processing domain, accessible datasets are crucial to reproduce and compare results. Publicly available implementations and tools can serve as benchmark and facilitate the development of more complex applications. However, in the context of clinical text processing the number of accessi...
Conference Paper
Tools and resources to automatically process clinical text are very limited, particularly outside the English speaking world. As many relevant patient information within electronic health records are described in unstructured text, this is a clear drawback. In order to slightly overcome this problem, we present information extraction models for Ger...
Preprint
Full-text available
Many people share information in social media or forums, like food they eat, sports activities they do or events which have been visited. This also applies to information about a person's health status. Information we share online unveils directly or indirectly information about our lifestyle and health situation and thus provides a valuable data r...
Conference Paper
Full-text available
Many people share information in social media or forums, like food they eat, sports activities they do or events which have been visited. This also applies to information about a person's health status. Information we share online unveils directly or indirectly information about our lifestyle and health situation and thus provides a valuable data r...

Citations

... First we ran an automatic annotation. This included the partial automatic labelling of the semantic layer using mEx (Roller et al., 2020) for named entity recognition and relation extraction. Although the schema of mEx partially differs, it includes various of our entities and is a good start to speed up the annotation. ...
... deleted messages) and the use of laymen terms and abbreviations (e.g. "AD" as a generic name for any anti-depressant) complicates the processing of these data (Seiffe et al., 2020;Basaldella et al., 2020). It is furthermore difficult to collect these resources (e.g. ...