EXTENDED DISTRIBUTED PROTOTYPICAL FOR BIOMEDICAL NAMED ENTITY RECOGNITION
Asia-Pacific Journal of Information Technology and Multimedia, 2017 Biomedical Named Entity Recognition (Bio-NER) is an essential step of biomedical information extraction and biomedical text mining. Although, a lot of researches have been made in the design of rule-based and supervised tools for general NER, Bio-NER ...
Maan Tareq Abd, Masnizah Mohd
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A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text Mining
IEEE Access, 2019 The amount of biomedical literature is vast and growing quickly, and accurate text mining techniques could help researchers to efficiently extract useful information from the literature.
Donghyeon Kim +8 more
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TPX: Biomedical literature search made easy [PDF]
, 2012 TPX is a web-based PubMed search enhancement tool that enables faster article searching using an alysis and exploration features . These features include identification of relevant biomedical concepts from search results with linkouts to source databases,
Aditya Rao +7 more
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Mining Images in Biomedical Publications: Detection and Analysis of Gel Diagrams [PDF]
, 2014 Authors of biomedical publications use gel images to report experimental results such as protein-protein interactions or protein expressions under different conditions. Gel images offer a concise way to communicate such findings, not all of which need to
Krauthammer, Michael +3 more
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Towards reliable named entity recognition in the biomedical domain [PDF]
Bioinformatics, 2019 Motivation: Automatic biomedical named entity recognition (BioNER) is a key task in biomedical information extraction (IE). For some time, state-of-the-art BioNER has been dominated by machine learning methods, particularly conditional random fields (CRFs), with a recent focus on deep learning.
Giorgi, John, Bader, Gary
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CRFVoter: gene and protein related object recognition using a conglomerate of CRF-based tools
Journal of Cheminformatics, 2019 Background Gene and protein related objects are an important class of entities in biomedical research, whose identification and extraction from scientific articles is attracting increasing interest.
Wahed Hemati, Alexander Mehler
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An annotated corpus with nanomedicine and pharmacokinetic parameters [PDF]
, 2017 A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP) approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction
Jimenez, Ivan +2 more
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A Bidirectional Iterative Algorithm for Nested Named Entity Recognition
IEEE Access, 2020 Nested named entity recognition (NER) is a special case of structured prediction in which annotated sequences can be contained inside each other. It is a challenging and significant problem in natural language processing.
Slawomir Dadas, Jaroslaw Protasiewicz
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A comparative study for biomedical named entity recognition
International Journal of Machine Learning and Cybernetics, 2015 With high-throughput technologies applied in biomedical research, the quantity of biomedical literatures grows exponentially. It becomes more and more important to quickly as well as accurately extract knowledge from manuscripts, especially in the era of big data.
Xu Wang, Chen Yang 0001, Renchu Guan
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OSIRISv1.2: a named entity recognition system for sequence variants of genes in biomedical literature [PDF]
, 2008 Background Single Nucleotide Polymorphisms, among other type of sequence variants, constitute key elements in genetic epidemiology and pharmacogenomics.
Laura I Furlong +39 more
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