Department of Medicine

Facilitating the use of artificial intelligence in healthcare

Sean Mooney, PhD

Chief Research Information Officer, UW Medicine
Interim Director, UW Institute for Medical Data Science
Associate Director, National Alzheimer's Coordinating Center (NACC)
Director Biomedical Informatics, Institute of Translational Health Sciences
Professor, Department of Biomedical Informatics and Medical Education
University of Washington

Why Attend this Seminar? 

It is an opportune time to be engaged in the research and application of informatics and artificial intelligence in biomedicine.  The increased use of electronic and personal health records and personal mobile devices is creating many opportunities at research academic medical centers.  At the University of Washington, I believe we are laying the ground work to build the informatics and information technology infrastructure to support research on personalized approaches and the use of data science to enable them. We are beginning to see the early successes of these efforts and I will describe some of them. But there are many challenges, for example, we continue to generate massive amounts of data that is largely uncurated. This includes images, genomes and other -omics datasets, personal monitors, electronic health records, etc. In this presentation, I will discuss our support of data for research use within UW Medicine, our efforts to build new machine learning and data science approaches using clinical datasets, and our efforts to develop new machine learning methods.  Further, we are leveraging the crowd by organizing and participating in community challenges (critical assessments) to build a better understanding of the types of approaches that perform well and in what context.  I will describe our involvement in the Institute of Translational Health Sciences, UW Medicine Information Technology Services, the Department of Biomedical Informatics and Medical Education and the newly founded Institute for Medical Data Science and how this collaboration is building upon a vision to enable research translation to clinical care with a particular emphasis on data science methodology.