Here are the research themes that the Health Data Science Lab (HDSL) is primarily interested in. Click on each theme and you will find a brief description of our research activities as well as links to key publications.
Critical care medicine is a data-intensive medical specialty that deals with a large amount of heterogeneous data on a daily basis. Although the volume and variety of critical care data pose many challenges, they also present interesting opportunities for health data science research.
Longitudinal data comprise a response that is measured repeatedly over time, for a number of individual units, in a study. This might include measurement of serum proteins from nephrology patients over time, measurements of smoking behaviour over time in a smoking cessation trial or observational study, or measures of air particulates in geographical regions over time.
Data visualization is a key component of health data science. Even brilliant data analytics may not end up being useful if the results are not communicated in an effective manner. Modern data visualization techniques provide some of the most powerful ways to interpret health data, information, and knowledge.
Mobile Health (mHealth) is one of the hottest fields in health informatics that has enormous potential in shifting routine health care from the hands of health care providers to those of everyone. While modern wearable devices generate continuous streams of diverse health data including physical activity, sleep quality, heart rate, and galvanic skin response, our everyday usage of smart phones and social media, as well as public information available on the Internet, provide important contextual information.