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Wednesday, October 3, 2018 at 11:00am to 12:00pm
Cornell Tech , Bloomberg 165 2 West Loop Road, NY NY 10044
"Integrative Mining of Heterogeneous Health Data"
The arrival of the Precision Medicine age brings tremendous opportunities to scientific discovery and quality improvement in medicine and healthcare. However, it also raises big challenges in dealing with large and massive healthcare data from heterogeneous sources. In this talk, I will present a series of research from my group on generating insights from complex healthcare data including Electronic Health Records (EHR), drug development data, neuroimaging data, etc. I will also point out the limitations of existing methodologies and future research directions.
Fei Wang is an Assistant Professor in Division of Health Informatics, Department of Healthcare Policy and Research, Weill Cornell Medicine, Cornell University. His major research interest is data mining, machine learning methodologies, as well as their applications in health data science. His papers have received over 6,600 citations so far with an H-index 43. His (or his students’) papers won best paper runner-up for ICDM 2016, ICHI 2016 best research paper award, best student paper for ICDM 2015, best research paper nomination for ICDM 2010, Marco Romani Best paper nomination in AMIA TBI 2014, and his paper was selected into the best paper finalist in SDM 2011 and 2015. He also won the Parkinson's Progression Markers' Initiative data challenge organized by Michael J. Fox Foundation, and NIPS 2017 challenge on Classification of Clinically Actionable Genetic Mutations. Dr. Wang is the chair-elect of the KDD working group in AMIA. Dr. Wang is an action editor of the journal Data Mining and Knowledge Discovery, an associate editor of Journal of Health Informatics Research, Smart Health, Pattern Recognition and IEEE Transactions on