student profile: Mr Andrew Goodwin


Thesis work

Thesis title: Probabilistic Data Quality Modelling in the Intensive Care Unit

Supervisors: Philip DE CHAZAL , Mark TRACY , Alistair MCEWAN

Thesis abstract:

�p�I aim to identify and quantify the uncertainties associated with high frequency physiological data collected in an intensive care environment. This will involve:�/p� �p�Modelling the accuracy and precision of every measurement in the ICU, including measurements in the temporal domain�/p� �p�Increasing the fidelity of stored physiological measurements by identifying and mitigating potential information loss in data pre-processing workflows�/p� �p�Examining any link between data quality and model performance.�/p� �p�Developing practical, model specific, signal quality indexes�/p� �p�Examining the cumulative impacts of measurement uncertainty on predictive analytics via robust error propagation approaches�/p� �p�Establishing a set of objective quality metrics that can be used to transfer metadata about physiological data collected at different sites.�/p�

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