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A Machine Learning Approach for Identifying Anatomical Locations of Actionable Findings in Radiology Reports
Recognizing the anatomical location of actionable findings in radiology reports is an important part of the communication of critical test results between caregivers. One of the difficulties of identifying anatomical locations of actionable findings stems from the fact that anatomical locations are...
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| Main Authors: | , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
American Medical Informatics Association
2012
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3540484/ https://ncbi.nlm.nih.gov/pubmed/23304352 |
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