Biomedical named entity recognition (BNER), which extracts important named entities such
as genes and proteins, is a challenging task in automated systems that mine knowledge in …

Motivation Best performing named entity recognition (NER) methods for biomedical literature
are based on hand-crafted features or task-specific rules, which are costly to produce and …

Abstract Named Entity Recognition is the process of identifying different entities in a given
context. Biomedical Named Entity Recognition (BNER) is the task of extracting chemical …

Background In biomedical text mining, named entity recognition (NER) is an important task
used to extract information from biomedical articles. Previously proposed methods for NER …

Background Biomedical named entity recognition (BNER) is a crucial initial step of
information extraction in biomedical domain. The task is typically modeled as a sequence …

Motivation State-of-the-art biomedical named entity recognition (BioNER) systems often
require handcrafted features specific to each entity type, such as genes, chemicals and …

Abstract Background Named Entity Recognition (NER) is a key task in biomedical text
mining. Accurate NER systems require task-specific, manually-annotated datasets, which …

Biomedical named entity recognition (BNER) is the basis of biomedical text mining and one
of the core sub-tasks of information extraction. Previous BNER models based on …

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

Background Automatic recognition of biomedical names is an essential task in biomedical
information extraction, presenting several complex and unsolved challenges. In recent …