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ADEPt, a semantically-enriched pipeline for extracting adverse drug events from free-text electronic health records
Adverse drug events (ADEs) are unintended responses to medical treatment. They can greatly affect a patient’s quality of life and present a substantial burden on healthcare. Although Electronic health records (EHRs) document a wealth of information relating to ADEs, they are frequently stored in the...
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| 出版年: | PLoS One |
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| 主要な著者: | , , , , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2017
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5679515/ https://ncbi.nlm.nih.gov/pubmed/29121053 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0187121 |
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