A Computing, Inference and Learning lab at Penn School of Medicine

Improving human health by prime insights from data

In the last decade, there has been major advances in the production and collection of data, from medical research to patient wellness regimes. These vast new troves of data from electronic health records, genetic/genomic databases, medical devices and wearables offer a unique opportunity to make health care more proactive. Transforming these data into insights requires deep understanding of the sampling/collection of the data, the intercorrelations among the variables, the quality of the data, and the uncertainty associated with the analytical results from models.
We are interested in working on developing, applying and disseminating novel methods and software for synthesizing evidence from clinical trial data and real world data, and for dealing with suboptimal quality issues of observational data. We aim to continue bridging the gap from data to insights, and from insights to actionable health care.