The paper gives an overview of a machine learning-based system developed to support
systematic literature reviews (SLR). The objective of the system is to provide scientists and …

The complexity of neurodegenerative diseases has motivated the development of artificial
intelligence approaches to predicting risk of impairment and disease progression. However …

Dataset Retrieval is gaining importance due to a large amount of research data and the
great demand for reusing scientific data. Dataset Retrieval is mostly based on metadata …

In this paper, we describe the approach and the results of our participation in task 1
(multilingual information extraction) of the CLEF eHealth 2020 challenge. We tackled the …

Identifying relevant studies and harmonizing datasets are major hurdles for data reuse.
Common Data Elements (CDEs) can help identify comparable study datasets and reduce …

The ever-growing availability of biomedical text sources has resulted in a boost in clinical
studies based on their exploitation. Biomedical named-entity recognition (bio-NER) …

Within the context of Twitter analytics, the notion of implicit entity linking has recently been
introduced to refer to the identification of a named entity, which is central to the topic of the …

A significant portion of biomedical literature is represented in a manner that makes it difficult
for consumers to find or aggregate content through a computational query. One approach to …

Featured Application Within the context of the Medical Informatics Initiative (MII) funded by
the Federal Ministry of Research and Education (BMBF), German academic medicine …

Given the ubiquity of unstructured biomedical data, significant obstacles still remain in
achieving accurate and fast access to online biomedical content. Accompanying semantic …