About the Center

Providing both research and business opportunities, the Center for Artificial Intelligence Driven Health Data Systems and Analytics was developed to address the rapid growth in clinical and biological data and leverage the ever-growing technological breakthroughs to expand 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 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.

This center brings together a multidisciplinary team of researchers drawn from the fields of medicine, biology, public health, informatics, computer science, applied mathematics, and statistics. Together, our mission is to improve the health of individuals and the healthcare system through data-driven methods and understanding of clinical processes—to engineer advanced descriptive, predictive, and prescriptive methods for medical disorders to the benefit of researchers, physicians, patients and caregivers.

Vision

To incorporate algorithmic and systems innovations into the study of biological and clinical datasets so as to enable new discoveries and to enhance healthcare delivery. 

This center will achieve this vision through innovations in i) computing and data management – creating a secure hub of high-quality curated datasets, ii) developing smart analytics for the extraction of actionable intelligence – learning from vast amounts of data to inform biologists and clinicians about biomarkers to pursue in the laboratory for experiments, or patient-specific therapeutic choices which maximize therapeutic success, and iii) systems innovations – designing special-purpose computing engines while seamlessly interfacing with multi-processor technologies.