Named entity recognition and relation detection for biomedical information extraction
The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …
Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives
J Xu, P Yang, S Xue, B Sharma, M Sanchez-Martin… - Human genetics, 2019 - Springer
In the field of cancer genomics, the broad availability of genetic information offered by next-
generation sequencing technologies and rapid growth in biomedical publication has led to …
generation sequencing technologies and rapid growth in biomedical publication has led to …
miRBase: from microRNA sequences to function
A Kozomara, M Birgaoanu… - Nucleic acids …, 2019 - academic.oup.com
Abstract miRBase catalogs, names and distributes microRNA gene sequences. The latest
release of miRBase (v22) contains microRNA sequences from 271 organisms: 38 589 …
release of miRBase (v22) contains microRNA sequences from 271 organisms: 38 589 …
PubTator central: automated concept annotation for biomedical full text articles
Abstract PubTator Central (https://www. ncbi. nlm. nih. gov/research/pubtator/) is a web
service for viewing and retrieving bioconcept annotations in full text biomedical articles …
service for viewing and retrieving bioconcept annotations in full text biomedical articles …
BERN2: an advanced neural biomedical named entity recognition and normalization tool
In biomedical natural language processing, named entity recognition (NER) and named
entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical …
entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical …
BioRED: a rich biomedical relation extraction dataset
Automated relation extraction (RE) from biomedical literature is critical for many downstream
text mining applications in both research and real-world settings. However, most existing …
text mining applications in both research and real-world settings. However, most existing …
TaggerOne: joint named entity recognition and normalization with semi-Markov Models
Motivation: Text mining is increasingly used to manage the accelerating pace of the
biomedical literature. Many text mining applications depend on accurate named entity …
biomedical literature. Many text mining applications depend on accurate named entity …
Information retrieval and text mining technologies for chemistry
Efficient access to chemical information contained in scientific literature, patents, technical
reports, or the web is a pressing need shared by researchers and patent attorneys from …
reports, or the web is a pressing need shared by researchers and patent attorneys from …
Biomedical entity representations with synonym marginalization
Biomedical named entities often play important roles in many biomedical text mining tools.
However, due to the incompleteness of provided synonyms and numerous variations in their …
However, due to the incompleteness of provided synonyms and numerous variations in their …
HunFlair: an easy-to-use tool for state-of-the-art biomedical named entity recognition
Named entity recognition (NER) is an important step in biomedical information extraction
pipelines. Tools for NER should be easy to use, cover multiple entity types, be highly …
pipelines. Tools for NER should be easy to use, cover multiple entity types, be highly …