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Characterization of Change and Significance for Clinical Findings in Radiology Reports Through Natural Language Processing
We built a natural language processing (NLP) method to automatically extract clinical findings in radiology reports and characterize their level of change and significance according to a radiology-specific information model. We utilized a combination of machine learning and rule-based approaches for...
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| 出版年: | J Digit Imaging |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer International Publishing
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5422225/ https://ncbi.nlm.nih.gov/pubmed/28050714 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10278-016-9931-8 |
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