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Clinical Data Extraction and Normalization of Cyrillic Electronic Health Records Via Deep-Learning Natural Language Processing
PURPOSE: A substantial portion of medical data is unstructured. Extracting data from unstructured text presents a barrier to advancing clinical research and improving patient care. In addition, ongoing studies have been focused predominately on the English language, whereas inflected languages with...
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| Publicado no: | JCO Clin Cancer Inform |
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| Autor principal: | |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
American Society of Clinical Oncology
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6874014/ https://ncbi.nlm.nih.gov/pubmed/31577448 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1200/CCI.19.00057 |
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