Bioinformatics, Electronic Medical Record Data, Epidemiology, Genetics, Genomics, Healthcare Management and Outcomes, Medical Imaging, Medical Informatics, Precision Health
Artificial Intelligence, Bayesian Methods, Data Mining, Decision Science, Deep Learning, Heterogeneous Data Integration, High-Dimensional Data Analysis, Image Data Processing and Analysis, Longitudinal Data Analysis, Machine Learning, Missing Data and Imputation, Natural Language Processing, Network Analysis, Pattern Analysis and Classification, Real-time Data Processing, Signal Processing, Statistical Inference, Statistical Modeling, Statistics

Christopher E. Gillies

Assistant Research Scientist

Emergency Medicine

I am Research Faculty with the Michigan Center for Integrative Research in Critical Care (MCIRCC). Our team builds predictive algorithms, analyzes signals, and implements statistical models to advance Critical Care Medicine. We use electronic healthcare record data to build predictive algorithms. One example of this is Predicting Intensive Care Transfers and other Unforeseen Events (PICTURE), which uses commonly collected vital signs and labs to predict patient deterioration on the general hospital floor. Additionally, our team collects waveforms from the University Hospital, and we store this data utilizing Amazon Web Services. We use these signals to build predictive algorithms to advance precision medicine. Our flagship algorithm called Analytic for Hemodynamic Instability (AHI), predicts patient deterioration using a single-lead electrocardiogram signal. We use Bayesian methods to analyze metabolomic biomarker data from blood and exhaled breath to understand Sepsis and Acute Respiratory Distress Syndrome. I also have an interest in statistical genetics.