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Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data
Building accurate predictive models of clinical multivariate time series is crucial for understanding of the patient condition, the dynamics of a disease, and clinical decision making. A challenging aspect of this process is that the model should be flexible and adaptive to reflect well patient-spec...
Guardado en:
| Publicado en: | Proc AAAI Conf Artif Intell |
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| Autores principales: | , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
2016
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4980099/ https://ncbi.nlm.nih.gov/pubmed/27525189 |
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