Cargando…
Automated SNOMED CT concept and attribute relationship detection through a web-based implementation of cTAKES
BACKGROUND: Information in Electronic Health Records is largely stored as unstructured free text. Natural language processing (NLP), or Medical Language Processing (MLP) in medicine, aims at extracting structured information from free text, and is less expensive and time-consuming than manual extrac...
Autores principales: | Kersloot, Martijn G., Lau, Francis, Abu-Hanna, Ameen, Arts, Derk L., Cornet, Ronald |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749652/ https://www.ncbi.nlm.nih.gov/pubmed/31533810 http://dx.doi.org/10.1186/s13326-019-0207-3 |
Ejemplares similares
-
Perceptions and behavior of clinical researchers and research support staff regarding data FAIRification
por: Kersloot, Martijn G., et al.
Publicado: (2022) -
Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies
por: Kersloot, Martijn G., et al.
Publicado: (2020) -
A survey of SNOMED CT implementations
por: Lee, Dennis, et al.
Publicado: (2013) -
Comparison of MetaMap and cTAKES for entity extraction in clinical notes
por: Reátegui, Ruth, et al.
Publicado: (2018) -
Forty years of SNOMED: a literature review
por: Cornet, Ronald, et al.
Publicado: (2008)