Kidney Epidemiology and Data Mining


Jundong Li, assistant professor, electrical and computer engineering

Jundong Li is an assistant professor in the Department of Electrical and Computer Engineering, with joint appointments in the Department of Computer Science and the School of Data Science. He is an expert in causal inference, data mining and machine learning techniques. In collaboration with faculty members in the UVA Division of Nephrology, Li is helping to mine medical record data to identify high risk drug combinations in patients with kidney disease. The average patient with advanced kidney failure, or end-stage kidney disease (ESKD), takes up to 12 distinct medications daily with a pill burden that can exceed 20 pills daily. Another large issue for ESKD patients is that they are routinely excluded from clinical trials because of their reduced kidney function. Therefore, these patients are often prescribed drugs that have not been tested for safet use in their population. Applying causal inference techniques to this data set, that includes a pharmaceutical history of use, will provide a new form of evaluation for medication safety in kidney disease and other fields.