The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …

Automated relation extraction (RE) from biomedical literature is critical for many downstream
text mining applications in both research and real-world settings. However, most existing …

Distributed word representations have become an essential foundation for biomedical
natural language processing (BioNLP), text mining and information retrieval. Word …

Motivation Text mining has become an important tool for biomedical research. The most
fundamental text-mining task is the recognition of biomedical named entities (NER), such as …

Text mining is a flexible technology that can be applied to numerous different tasks in
biology and medicine. We present a system for extracting disease–gene associations from …

Named entity recognition (NER) is an important step in biomedical information extraction
pipelines. Tools for NER should be easy to use, cover multiple entity types, be highly …

Motivation The explosive increase of biomedical literature has made information extraction
an increasingly important tool for biomedical research. A fundamental task is the recognition …

Motivation: The discovery of regulatory pathways, signal cascades, metabolic processes or
disease models requires knowledge on individual relations like eg physical or regulatory …

The fields of medicine science and health informatics have made great progress recently
and have led to in-depth analytics that is demanded by generation, collection and …

For the average biologist, hands-on literature mining currently means a keyword search in
PubMed. However, methods for extracting biomedical facts from the scientific literature have …