Funded in part by the Grainger Foundation, an independent, private foundation the Center for Artificial Intelligence Driven Health Data Systems and Analytics was developed to address the rapid growth in clinical and biological data and the ever-growing technological breakthroughs and limited knowledge about the science of key diseases. It is this opportunity to transform medicine through the powers of computing and algorithmic innovations that is at the core of the Center for Artificial Intelligence Driven Health Data Systems and Analytics.

Working with industry and hospital partners our challenge is to jointly analyze a variety of large, diverse and complex clinical and biological data that is static and longitudinal in nature by bringing together cutting-edge analytics, machine learning and systems engineering expertise to generate what we call Actionable Intelligence (small but valuable predictive patient specific clinical information) to drive Systems Innovation.

The Center will address three major challenges:

1. Develop large and standardized medical data: Data-driven techniques including the cutting edge deep learning/AI techniques require large and well-curated datasets from across the health care landscape.
2. Advanced analytical techniques for healthcare: Expand data-driven and machine learning techniques curate and harmonize large datasets. Computer scientists scale the infrastructure and algorithms; visualization experts enhance user understanding of the data, and interdisciplinary teams of physicians, biologists, clinicians validate and interpret the algorithms and results. Ultimately, these techniques could lead to new robotics and automation systems.
3. Significant computation and storage resources: Big data and AI demands huge datasets and computation to create appropriate models, often exceeding the capacity of conventional health care community computing facilities even though the inferencing engines applying the models can be mass produced inexpensively.