Efficient access to chemical information contained in scientific literature, patents, technical
reports, or the web is a pressing need shared by researchers and patent attorneys from …

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 …

Motivation: Text mining is increasingly used to manage the accelerating pace of the
biomedical literature. Many text mining applications depend on accurate named entity …

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 …

Highlights•Text mining techniques can unlock the information stored in biomedical
patents.•Most research in mining such patents is limited to identifying terms.•Future …

Motivation Biomedical named entity recognition (BioNER) seeks to automatically recognize
biomedical entities in natural language text, serving as a necessary foundation for …

Chemical patents represent a valuable source of information about new chemical
compounds, which is critical to the drug discovery process. Automated information extraction …

Motivation Several recent studies showed that the application of deep neural networks
advanced the state-of-the-art in named entity recognition (NER), including biomedical NER …

Advancing the state-of-the-art in large-scale biomedical semantic indexing and question
answering is the main focus of the BioASQ challenge. BioASQ organizes respective tasks …