BDI Seminar: Hospital patient time series data: Statistical models for associations and decision making
Professor Barbara Engelhardt, Computer Science Department, Princeton University
Tuesday, 12 June 2018, 4pm to 5pm
BDI Seminar Room 0, Big Data Institute, Oxford, OX3 7LF
In-patient hospital data presents unique challenges for time series analysis, including the sparsity and irregularity of observations for each patient and the heterogeneous patient responses to interventions. In this talk, I will present a multi-output Gaussian process regression model for patient time series data that captures the state of a patient and uncertainty in this state across four vital signs and 20 lab tests in a patient-specific way. We build on top of this model a reinforcement learning approach to assist doctors to wean patients from a mechanical ventilator. Finally, I show how prior work with time series associations may be used with these data to identify patients with genetically-mediated responses to specific interventions. I will conclude with directions for future work.