Data pre-processing using neural processes for modelling personalised vital-sign time-series data
Clinical time-series data retrieved from electronic medical records are widely used to build predictive models of adverse events to support resource management. Such data is often sparse and irregularly-sampled, which makes it challenging to use many common machine learning methods. Missing values m...
| Autori principali: | , , , |
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| Natura: | Journal article |
| Lingua: | English |
| Pubblicazione: |
IEEE
2021
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