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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...
Uloženo v:
| Vydáno v: | AMIA Annu Symp Proc |
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| Hlavní autoři: | , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
American Medical Informatics Association
2017
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5333249/ https://ncbi.nlm.nih.gov/pubmed/28269852 |
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