The recent years have witnessed a rapid increase in the number of scientific articles in
biomedical domain. These literature are mostly available and readily accessible in …

The emergence of “big data” initiatives has led to the need for tools that can automatically
extract valuable chemical information from large volumes of unstructured data, such as the …

Text mining is a powerful technology for quickly distilling key information from vast quantities
of biomedical literature. However, to harness this power the researcher must be well versed …

Motivation The biomedical community's collective understanding of how chemicals, genes
and phenotypes interact is distributed across the text of over 24 million research articles …

Motivation The overwhelming size and rapid growth of the biomedical literature make it
impossible for scientists to read all studies related to their work, potentially leading to missed …

Background Many biomedical relation extraction systems are machine-learning based and
have to be trained on large annotated corpora that are expensive and cumbersome to …

The identification of medical concepts from clinical narratives has a large interest in the
biomedical scientific community due to its importance in treatment improvements or drug …

Background Timely data is key to effective public health responses to epidemics. Drug
overdose deaths are identified in surveillance systems through ICD-10 codes present on …

Relation extraction (RE) is a fundamental task for extracting gene–disease associations from
biomedical text. Many state-of-the-art tools have limited capacity, as they can extract gene …

Sentence boundary detection (SBD) is a critical preprocessing task for many natural
language processing (NLP) applications. However, there has been little work on evaluating …