Deep Learning-Based Recurrent Prediction of Delirium in the Intensive Care Unit
Joon Lee
May 3, 2023, Wednesday, 3:00 PM - 4:00 PM EDT
Delirium is common in the intensive care unit (ICU) and associated with longer ICU and hospital stays as well as worse patient outcomes including long-term cognitive impairment. Early prediction of impending delirium can lead to efficient allocation of ICU resources and improved patient outcomes via preventive care. Based on rich clinical data from over 43,000 ICU admissions in Alberta, we developed deep learning-based models capable of predicting delirium in the next two 12-hour windows, with new predictions generated every 12 hours. Our best model based on gated recurrent units resulted in areas under the receiver operating characteristic curve around 0.9.
Dr. Joon Lee is an Associate Professor of Health Data Science in the Departments of Community Health Sciences & Cardiac Sciences, Cumming School of Medicine, University of Calgary, and the Director of the Data Intelligence for Health Lab. He is also a member of the Libin Cardiovascular Institute of Alberta and the O'Brien Institute for Public Health.

He holds a PhD in Biomedical Engineering from the University of Toronto, and a BASc in Electrical Engineering from the University of Waterloo. He also completed a postdoctoral fellowship in Medical Data Science at the Harvard-MIT Division of Health Sciences and Technology. Prior to joining the University of Calgary, he held a faculty appointment in the School of Public Health and Health Systems, Faculty of Applied Health Sciences, University of Waterloo, for 6 years.

His primary research interest is in transforming health data from various sources into useful information and knowledge. His research applies data science, machine learning, artificial intelligence, natural language processing, mobile technology, and biostatistics to several health fields including intensive care medicine, aging, and population health surveillance. His up-to-date publication list is available on Google Scholar.

In 2016, he received an Early Researcher Award from the Ontario Ministry of Research, Innovation and Science.