Our informatics faculty members actively develop new methodology in artificial intelligence, natural-language processing and machine learning. These methods make possible novel analyses of clinical data from electronic-health records and of data from population-based studies of common diseases, such as asthma and cancer.

Computational models of human health must take into account its complexity—how it is impacted by the interplay of demographic, environmental and genomic factors. The DBEI brings the informatics faculty’s work into close proximity and collaboration with cutting-edge research in biostatistics and epidemiology, connecting the questions we can ask about an individual with those we can ask at the population level.  We invite you to explore some of their findings here.