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Representation learning for clinical time series prediction tasks in electronic health records
BACKGROUND: Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high dimensionality, sparseness, noise, random error and systematic bias. In particu...
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| Publicado no: | BMC Med Inform Decis Mak |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6916209/ https://ncbi.nlm.nih.gov/pubmed/31842854 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12911-019-0985-7 |
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