The rapid increase in the flow rate of published digital information in all disciplines has
resulted in a pressing need for techniques that can simplify the use of this information. The …

Drug name recognition (DNR), which seeks to recognize drug mentions in unstructured
medical texts and classify them into pre-defined categories, is a fundamental task of medical …

Medicinal chemistry patents contain rich information about chemical compounds. Although
much effort has been devoted to extracting chemical entities from scientific literature, limited …

Background: Drug prescriptions are often recorded in free-text clinical narratives; making
this information available in a structured form is important to support many health-related …

Speculations represent uncertainty toward certain facts. In clinical texts, identifying
speculations is a critical step of natural language processing (NLP). While it is a nontrivial …

Biomedical Named Entity Recognition (BNER) is the task of identifying biomedical instances
such as chemical compounds, genes, proteins, viruses, disorders, DNAs and RNAs. The key …

We investigate the quality of task specific word embeddings created with relatively small,
targeted corpora. We present a comprehensive evaluation framework including both intrinsic …

Background and objectives Researchers have developed effective methods to index free-
text clinical notes into structured database, in which negation detection is a critical but …

Biomedical Entity extraction is the process of identifying biomedical instances such as
disorders, viruses, proteins, genes and others. One of these instances is the chemical …

The large, and increasing, number of chemical compounds poses challenges to the
exploration of such datasets. In this work, we propose the usage of recommender systems to …