Configurable web-services for biomedical document annotation
Journal of Cheminformatics, 2018 The need to efficiently find and extract information from the continuously growing biomedical literature has led to the development of various annotation tools aimed at identifying mentions of entities and relations.
Sérgio Matos
doaj +1 more source
Study of Named Entity Recognition methods in biomedical field
Procedia Computer Science, 2019 Abstract Natural Language Processing (NLP) is very important in modern data processing taking into consideration different sources, forms and purpose of data as well as information in different areas our industry, administration, public and private life. Our studies concern Natural Language Processing techniques in biomedical field.
Anna Sniegula +2 more
openaire +1 more source
A neural network approach to chemical and gene/protein entity recognition in patents
Journal of Cheminformatics, 2018 In biomedical research, patents contain the significant amount of information, and biomedical text mining has received much attention in patents recently.
Ling Luo +6 more
doaj +1 more source
A Survey of Named-Entity Recognition Methods for Food Information Extraction
IEEE Access, 2020 As great amounts of food-related information is presented in the form of heterogeneous textual data, computer-based methods are useful to automatically extract such information. One way to do this is to utilize Named-Entity Recognition (NER) methods that
Gorjan Popovski +2 more
doaj +1 more source
Unsupervised Biomedical Named Entity Recognition [PDF]
, 2017 Named entity recognition (NER) from text is an important task for several applications, including in the biomedical domain. Supervised machine learning based systems have been the most successful on NER task, however, they require correct annotations in ...
Ghiasvand, Omid
core +1 more source
Optimising Selective Sampling for Bootstrapping Named Entity Recognition [PDF]
, 2005 Training a statistical named entity recognition system in a new domain requires costly manual annotation of large quantities of in-domain data. Active learning promises to reduce the annotation cost by selecting only highly informative data points.
Alex, Beatrice +3 more
core +1 more source
Discovering Power Laws in Entity Length
, 2018 This paper presents a discovery that the length of the entities in various datasets follows a family of scale-free power law distributions. The concept of entity here broadly includes the named entity, entity mention, time expression, aspect term, and ...
Cambria, Erik +2 more
core
Biomedical named entity recognition based on fusion multi-features embedding. [PDF]
Technol Health Care, 2023 Li M, Yang H, Liu Y.
europepmc +1 more source
AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning. [PDF]
Bioinformatics, 2023 Luo L +5 more
europepmc +1 more source
Few-shot biomedical named entity recognition via knowledge-guided instance generation and prompt contrastive learning. [PDF]
Bioinformatics, 2023 Chen P, Wang J, Lin H, Zhao D, Yang Z.
europepmc +1 more source