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Towards Comprehensive Clinical Abbreviation Disambiguation Using Machine-Labeled Training Data
Abbreviation disambiguation in clinical texts is a problem handled well by fully supervised machine learning methods. Acquiring training data, however, is expensive and would be impractical for large numbers of abbreviations in specialized corpora. An alternative is a semi-supervised approach, in wh...
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| I publikationen: | AMIA Annu Symp Proc |
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| Huvudupphovsmän: | , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
American Medical Informatics Association
2017
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5333249/ https://ncbi.nlm.nih.gov/pubmed/28269852 |
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