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Ensembles of randomized trees using diverse distributed representations of clinical events
BACKGROUND: Learning deep representations of clinical events based on their distributions in electronic health records has been shown to allow for subsequent training of higher-performing predictive models compared to the use of shallow, count-based representations. The predictive performance may be...
Tallennettuna:
| Julkaisussa: | BMC Med Inform Decis Mak |
|---|---|
| Päätekijät: | , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
BioMed Central
2016
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4965720/ https://ncbi.nlm.nih.gov/pubmed/27459846 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12911-016-0309-0 |
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