Cargando…
Evaluation of a Concept Mapping Task Using Named Entity Recognition and Normalization in Unstructured Clinical Text
In this pilot study, we explore the feasibility and accuracy of using a query in a commercial natural language processing engine in a named entity recognition and normalization task to extract a wide spectrum of clinical concepts from free text clinical letters. Editorial guidance developed by two i...
Autores principales: | Trivedi, Sapna, Gildersleeve, Roger, Franco, Sandra, Kanter, Andrew S., Chaudhry, Afzal |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982815/ https://www.ncbi.nlm.nih.gov/pubmed/35415451 http://dx.doi.org/10.1007/s41666-020-00079-z |
Ejemplares similares
-
MLM-based typographical error correction of unstructured medical texts for named entity recognition
por: Lee, Eun Byul, et al.
Publicado: (2022) -
Text normalization for named entity recognition in Vietnamese tweets
por: Nguyen, Vu H., et al.
Publicado: (2016) -
Impact of translation on named-entity recognition in radiology texts
por: Campos, Luís, et al.
Publicado: (2017) -
Named Entity Recognition of Medical Text Based on the Deep Neural Network
por: Yang, Tianjiao, et al.
Publicado: (2022) -
Evaluating Word Representation Features in Biomedical Named Entity Recognition Tasks
por: Tang, Buzhou, et al.
Publicado: (2014)