Objectives Biomedical natural language processing tools are increasingly being applied for
broad-coverage information extraction—extracting medical information of all types in a …

Automatic identification and expansion of ambiguous abbreviations are essential for
biomedical natural language processing applications, such as information retrieval and …

Objective In biomedicine, there is a wealth of information hidden in unstructured narratives
such as research articles and clinical reports. To exploit these data properly, a word sense …

Biomedical words have many semantics. Biomedical word sense disambiguation (WSD) is
an important research issue in biomedicine field. Biomedical WSD refers to the process of …

In order to improve the disambiguation accuracy of biomedical words, this paper proposes a
disambiguation method based on the attention neural network. The biomedical word is …

Semantic mining is always a challenge for big biomedical text data. Ontology has been
widely proved and used to extract semantic information. However, the process of ontology …

The scientific literature contains large amounts of information on genes, proteins, chemicals
and their interactions. Extraction and integration of this information in curated knowledge …

Extracting Chemical- Protein Interactions using Long Short-Term Memory Networks Page 1
Extracting ChemicalProtein Interactions using Long Short-Term Memory Networks Sérgio Matos …

Automating text simplification is a challenging research area due to the compound structures
present in natural languages. Social involvement of people with language deficits can be …

Temporal expression recognition and normalization (TERN) is the foundation for all higher-
level temporal reasoning tasks in natural language processing, such as timeline extraction …