State-space approximations to Gaussian processes for patient vital-sign monitoring in computationally-constrained clinical environments
Gaussian processes (GPs) define a probability distribution over a space of functions from which a set of observed data are assumed to be generated. When applied to a time-series of patient vital-sign data, GP models (i) can encode prior clinical knowledge of the dynamics of the data; (ii) are patien...
| Main Authors: | , , , |
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| 格式: | Conference item |
| 出版: |
2016
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