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Evaluating shallow and deep learning strategies for the 2018 n2c2 shared task on clinical text classification
OBJECTIVE: Automated clinical phenotyping is challenging because word-based features quickly turn it into a high-dimensional problem, in which the small, privacy-restricted, training datasets might lead to overfitting. Pretrained embeddings might solve this issue by reusing input representation sche...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6798565/ https://www.ncbi.nlm.nih.gov/pubmed/31512729 http://dx.doi.org/10.1093/jamia/ocz149 |