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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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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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American Society of Clinical Oncology
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874014/ https://www.ncbi.nlm.nih.gov/pubmed/31577448 http://dx.doi.org/10.1200/CCI.19.00057 |