Deploying and sharing U-Compare workflows as web services [PDF]
, 2013 BACKGROUND: U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain.
Ananiadou, Sophia +4 more
core +3 more sources
bioRxiv, 2020 Neural language representation models such as BERT [1] have recently shown state of the art performance in downstream NLP tasks and bio-medical domain adaptation of BERT (Bio-BERT [2]) has shown same behavior on biomedical text mining tasks. However, due
I. B. Ozyurt
semanticscholar +1 more source
Overview of biomedical relations extraction using hybrid rule-based approaches. [PDF]
, 2013 Unstructured text documents are the major source of knowledge in biomedical fields. These huge amounts of information cause very difficult task of extraction or classification.Therefore, there is a need for knowledge discovery and text mining tools in ...
Abdul Kadir, Rabiah +1 more
core +1 more source
Selecting an ontology for biomedical text mining [PDF]
Proceedings of the Workshop on BioNLP - BioNLP '09, 2009 Text mining for biomedicine requires a significant amount of domain knowledge. Much of this information is contained in biomedical ontologies. Developers of text mining applications often look for appropriate ontologies that can be integrated into their systems, rather than develop new ontologies from scratch.
He Tan, Patrick Lambrix
openaire +1 more source
Biomedical event extraction based on GRU integrating attention mechanism
BMC Bioinformatics, 2018 Background Biomedical event extraction is a crucial task in biomedical text mining. As the primary forum for international evaluation of different biomedical event extraction technologies, BioNLP Shared Task represents a trend in biomedical text mining ...
Lishuang Li +3 more
doaj +1 more source
Semi-supervised prediction of protein interaction sentences exploiting semantically encoded metrics [PDF]
, 2009 Protein-protein interaction (PPI) identification is an integral component of many biomedical research and database curation tools. Automation of this task through classification is one of the key goals of text mining (TM).
D.D. Lewis +14 more
core +2 more sources
Cell line name recognition in support of the identification of synthetic lethality in cancer from text [PDF]
, 2015 Motivation: The recognition and normalization of cell line names in text is an important task in biomedical text mining research, facilitating for instance the identification of synthetically lethal genes from the literature.
Ginter, Filip +5 more
core +2 more sources
Text Mining for Building Biomedical Networks Using Cancer as a Case Study
Biomolecules, 2021 In the assembly of biological networks it is important to provide reliable interactions in an effort to have the most possible accurate representation of real-life systems.
Sofia I R Conceição +1 more
semanticscholar +1 more source
The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge [PDF]
, 2016 Biomedical text mining methods and technologies have improved significantly in the last decade. Considerable efforts have been invested in understanding the main challenges of biomedical literature retrieval and extraction and proposing solutions to ...
Alfonso Valencia +12 more
core +1 more source
A Novel Multi-View Ensemble Learning Architecture to Improve the Structured Text Classification
Information, 2022 Multi-view ensemble learning exploits the information of data views. To test its efficiency for full text classification, a technique has been implemented where the views correspond to the document sections.
Carlos Adriano Gonçalves +5 more
doaj +1 more source