Cargando…
A crowdsourcing workflow for extracting chemical-induced disease relations from free text
Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative m...
Autores principales: | Li, Tong Shu, Bravo, Àlex, Furlong, Laura I., Good, Benjamin M., Su, Andrew I. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4834205/ https://www.ncbi.nlm.nih.gov/pubmed/27087308 http://dx.doi.org/10.1093/database/baw051 |
Ejemplares similares
-
Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text
por: Bravo, Àlex, et al.
Publicado: (2016) -
Data Centric Workflows for Crowdsourcing
por: Bourhis, Pierre, et al.
Publicado: (2020) -
Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research
por: Bravo, Àlex, et al.
Publicado: (2015) -
The Cure: Design and Evaluation of a Crowdsourcing Game for Gene Selection for Breast Cancer Survival Prediction
por: Good, Benjamin M, et al.
Publicado: (2014) -
Validation and tuning of in situ transcriptomics image processing workflows with crowdsourced annotations
por: Vo-Phamhi, Jenny M., et al.
Publicado: (2021)