Named entity recognition is critical for biomedical text mining, where it is not unusual to find entities labeled by a wide range of different terms. Nowadays, ontologies are one of the crucial enabling technologies in bioinformatics, providing resources for improved natural language processing tasks. However, biomedical ontology-based named entity recognition continues to be a major research problem.The work was supported by National Institute of Health Carlos III (grant no. FIS2012-PI12/00373) and FEDER (European funding)S
Supplementary material related to this article can be found online at https://doi.org/10.1016/j.eswa...
Background: This article describes a high-recall, high-precision approach for the extraction of biom...
Supplementary information: Full list of the 20 synonyms generated by our method from the release of ...
Abstract Background Named entity recognition is critical for biomedical text mining, where it is not...
MOTIVATION: Automatic phenotype concept recognition from unstructured text remains a challenging tas...
BACKGROUND Biomedical ontologies contain a wealth of metadata that constitutes a fundamental infr...
Concept recognition tools rely on the availability of textual corpora to assess their performance an...
Named-Entity Recognition is commonly used to identify biological entities such as proteins, genes, a...
<div><p>Synonymous relationships among biomedical terms are extensively annotated within specialized...
Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing...
Abstract Background Automatic identification of term variants or acceptable alternative free-text te...
Background Automatic identification of term variants or acceptable alternative free-text terms for g...
AbstractNamed entity recognition is a crucial component of biomedical natural language processing, e...
Due to the rapidly increasing amount of biomedical literature, automatic processing of biomedical pa...
Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing...
Supplementary material related to this article can be found online at https://doi.org/10.1016/j.eswa...
Background: This article describes a high-recall, high-precision approach for the extraction of biom...
Supplementary information: Full list of the 20 synonyms generated by our method from the release of ...
Abstract Background Named entity recognition is critical for biomedical text mining, where it is not...
MOTIVATION: Automatic phenotype concept recognition from unstructured text remains a challenging tas...
BACKGROUND Biomedical ontologies contain a wealth of metadata that constitutes a fundamental infr...
Concept recognition tools rely on the availability of textual corpora to assess their performance an...
Named-Entity Recognition is commonly used to identify biological entities such as proteins, genes, a...
<div><p>Synonymous relationships among biomedical terms are extensively annotated within specialized...
Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing...
Abstract Background Automatic identification of term variants or acceptable alternative free-text te...
Background Automatic identification of term variants or acceptable alternative free-text terms for g...
AbstractNamed entity recognition is a crucial component of biomedical natural language processing, e...
Due to the rapidly increasing amount of biomedical literature, automatic processing of biomedical pa...
Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing...
Supplementary material related to this article can be found online at https://doi.org/10.1016/j.eswa...
Background: This article describes a high-recall, high-precision approach for the extraction of biom...
Supplementary information: Full list of the 20 synonyms generated by our method from the release of ...