Predictive analytics in an intensive care unit by processing streams of physiological data in real-time

There has been increasing research into the application of machine learning techniques on these data streams to predict and prevent disease states, however limitations exist around understanding the optimal methods and availability of data to train such models which is what we aim to address in this thesis.

This thesis provides an insight into the work that has already been carried out in this field and further presents state-of-the-art research of AI for prediction of physiological data across two problem domains. This thesis features a description of the first Northern Ireland research-based ICU database that will enable further research to advance the field, of which we have set up. We compare machine learning methods for the classification of cardiovascular disease.