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Machine Learning Approaches to Identify Nicknames from A Statewide Health Information Exchange
Patient matching is essential to minimize fragmentation of patient data. Existing patient matching efforts often do not account for nickname use. We sought to develop decision models that could identify true nicknames using features representing the phonetical and structural similarity of nickname p...
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| Publié dans: | AMIA Jt Summits Transl Sci Proc |
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| Auteurs principaux: | , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
American Medical Informatics Association
2019
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6568128/ https://ncbi.nlm.nih.gov/pubmed/31259019 |
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