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From free text to clusters of content in health records: an unsupervised graph partitioning approach
Electronic healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed information often remains under-used in practice because of a lack of suitable methodologies to extract interpretable co...
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| Опубликовано в: : | Appl Netw Sci |
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| Главные авторы: | , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer International Publishing
2019
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6400329/ https://ncbi.nlm.nih.gov/pubmed/30906850 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s41109-018-0109-9 |
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