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Natural language processing systems for pathology parsing in limited data environments with uncertainty estimation
OBJECTIVE: Cancer is a leading cause of death, but much of the diagnostic information is stored as unstructured data in pathology reports. We aim to improve uncertainty estimates of machine learning-based pathology parsers and evaluate performance in low data settings. MATERIALS AND METHODS: Our dat...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751177/ https://www.ncbi.nlm.nih.gov/pubmed/33381748 http://dx.doi.org/10.1093/jamiaopen/ooaa029 |