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Clinical Word Sense Disambiguation with Interactive Search and Classification
Resolving word ambiguity in clinical text is critical for many natural language processing applications. Effective word sense disambiguation (WSD) systems rely on training a machine learning based classifier with abundant clinical text that is accurately annotated, the creation of which can be costl...
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| Publicado en: | AMIA Annu Symp Proc |
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| Autores principales: | , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
American Medical Informatics Association
2017
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5333264/ https://ncbi.nlm.nih.gov/pubmed/28269966 |
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