Population-level gaussian processes for clinical time series forecasting
Abstract:
A device, system and method for generating a prediction model for a test patient. To generate the prediction model, a multi-dimensional clinical time series for each of a plurality of training patients is collected to generate a training population. A machine learning algorithm is then trained using the training population. Measurement data corresponding to the test patient is also received, the measurement data includes a multi-dimensional clinical time series for the test patient. The test patient is not included in the plurality of training patients. The prediction model is generated for the test patient based on i) the measurement data corresponding to the test patient and ii) training the machine learning algorithm using the training population.
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