Deep learning methods for biomedical named entity recognition: a survey and qualitative comparison
The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …
from the large amount of literature is increasingly important. Biomedical 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 …
CHEMDNER: The drugs and chemical names extraction challenge
Natural language processing (NLP) and text mining technologies for the chemical domain
(ChemNLP or chemical text mining) are key to improve the access and integration of …
(ChemNLP or chemical text mining) are key to improve the access and integration of …
[HTML][HTML] Character level and word level embedding with bidirectional LSTM–Dynamic recurrent neural network for biomedical named entity recognition from literature
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 …
context. Biomedical Named Entity Recognition (BNER) is the task of extracting chemical …
Improving biomedical named entity recognition with syntactic information
Background Biomedical named entity recognition (BioNER) is an important task for
understanding biomedical texts, which can be challenging due to the lack of large-scale …
understanding biomedical texts, which can be challenging due to the lack of large-scale …
Chemu 2020: Natural language processing methods are effective for information extraction from chemical patents
Chemical patents represent a valuable source of information about new chemical
compounds, which is critical to the drug discovery process. Automated information extraction …
compounds, which is critical to the drug discovery process. Automated information extraction …
Automatic identification of relevant chemical compounds from patents
SA Akhondi, H Rey, M Schwörer, M Maier, J Toomey… - Database, 2019 - academic.oup.com
In commercial research and development projects, public disclosure of new chemical
compounds often takes place in patents. Only a small proportion of these compounds are …
compounds often takes place in patents. Only a small proportion of these compounds are …
Improving biomedical named entity recognition through transfer learning and asymmetric tri-training
M Bhattacharya, S Bhat, S Tripathy, A Bansal… - Procedia Computer …, 2023 - Elsevier
Today, electronic health records have turned into prime sources of information for physicians
looking after their patients. EHRs and computerized patient data resources have expedited …
looking after their patients. EHRs and computerized patient data resources have expedited …
Putting hands to rest: efficient deep CNN-RNN architecture for chemical named entity recognition with no hand-crafted rules
I Korvigo, M Holmatov, A Zaikovskii… - Journal of …, 2018 - Springer
Chemical named entity recognition (NER) is an active field of research in biomedical natural
language processing. To facilitate the development of new and superior chemical NER …
language processing. To facilitate the development of new and superior chemical NER …
A prefix and attention map discrimination fusion guided attention for biomedical named entity recognition
Z Guan, X Zhou - BMC bioinformatics, 2023 - Springer
Background The biomedical literature is growing rapidly, and it is increasingly important to
extract meaningful information from the vast amount of literature. Biomedical named entity …
extract meaningful information from the vast amount of literature. Biomedical named entity …