Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features

BACKGROUND: Named entity recognition (NER) is an important task in clinical natural language processing (NLP) research. Machine learning (ML) based NER methods have shown good performance in recognizing entities in clinical text. Algorithms and features are two important factors that largely affect...

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Detalles Bibliográficos
Autores principales: Tang, Buzhou, Cao, Hongxin, Wu, Yonghui, Jiang, Min, Xu, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3618243/
https://www.ncbi.nlm.nih.gov/pubmed/23566040
http://dx.doi.org/10.1186/1472-6947-13-S1-S1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3618243/
https://www.ncbi.nlm.nih.gov/pubmed/23566040
http://dx.doi.org/10.1186/1472-6947-13-S1-S1

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