A Bayesian Look At Clinical Risk Prediction
A Bayesian Look At Clinical Risk Prediction


Building reliable predictive and prognostic models that leverage the growing scale of medical data and clinical records can make tremendous impact to the healthcare industry. Traditional survival analysis originated from clinical research focuses on identifying variates and factors that affect the hazard function; time series modelling approaches emphasize predicting future values based on previous observations; machine learning models are often formulated as mapping between large feature spaces to binary outcomes. However, all of these methods have their unique limitations and there are still much more to explore in the context of treating clinical survival analysis with machine learning models. In this talk, we will present our recent work on a new Bayesian framework that uniquely connects machine learning tasks (classification/regression) with event time analysis to provide risk prediction capabilities. We validate and demonstrate the utility of this approach with simulation data where the ground truths are known. We will then show a specific use case of this approach to perform risk prediction with real medical datasets. We will also discuss how this model can be implemented into clinical solutions.


Dr. Luo works at Wolters Kluwer Health as an applied data scientist since 2017. With a strong belief in the power of AI and big data, he brings his expertise in machine learning and natural language processing to solve the most challenging problems in healthcare, for example, early prediction of diseases from EHR data. Before Wolters Kluwer, he worked at T2 Biosystems, developing novel medical devices for sepsis detect and blood test. Dr. Luo got his Ph.D. in physics from UNC Chapel Hill and had a dozen publications and three patent applications.

Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google