This is the idea

We extract meaning from health data.

Access to data has transformed the way entire industries interact with individuals—as consumers, voters, genomes, and more—but health data are still analyzed with methods developed in the 19th century.

Our work applies methods from machine learning, biostatistics, and econometrics to the complex world of medical diagnoses, interventions, and outcomes.

Our goal is to translate large observational datasets into new ways to understand and improve the life and death decisions that providers and patients make every day, in the US and across the world.

A joint lab at UC Berkeley and the University of Chicago