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Synthesize high-dimensional longitudinal electronic health records via hierarchical autoregressive language model
Synthetic electronic health records (EHRs) that are both realistic and privacy-preserving offer alternatives to real EHRs for machine learning (ML) and statistical analysis. However, generating high-fidelity EHR data in its original, high-dimensional form poses challenges for existing methods. We pr...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471716/ https://www.ncbi.nlm.nih.gov/pubmed/37652934 http://dx.doi.org/10.1038/s41467-023-41093-0 |