Data Science Speaker Series at UofT: Jessica Gronsbell on "Statistical Learning With Electronic Health Records Data"

Jan 18, 2021
|
5:15pm–6:15pm
Workshop/Seminar
Details

Learn about “Statistical Learning With Electronic Health Records Data” at the Data Science Speaker Series at U of T.

Join us online on January 18 to hear from Jessica Gronsbell, who is Assistant Professor in the Department of Statistical Sciences at the University of Toronto, as she draws reliable insights from imperfect electronic health records using a mix of classical statistical theory and modern machine learning tools.

Her talk will primarily focus on the challenges in obtaining annotated outcome data from patient records and how leveraging unlabeled examples to improve model estimation and evaluation can reduce the annotation burden.

You will be able to ask questions live!

The session will be moderated by CANSSI Ontario Director and Department of Statistical Sciences Professor Dr. Lisa Strug.

The Data Science Speaker Series at U of T (DSSS) is the result of a collaboration of Data Science programs at the University of Toronto: the Master of Science in Applied Computing (MScAC) in the Department of Computer Science, the Master of Management Analytics at the Rotman School of Management, and CANSSI Ontario.

Together, we seek to advance knowledge in the field of data science by featuring world-class speakers from academic, healthcare, industry, finance, technology, sports, and other sectors and industries.

Location
Online (by Zoom)
2021-01-18 22:15:00 2021-01-18 23:15:00 UTC Data Science Speaker Series at UofT: Jessica Gronsbell on "Statistical Learning With Electronic Health Records Data" Learn about “Statistical Learning With Electronic Health Records Data” at the Data Science Speaker Series at U of T.Join us online on January 18 to hear from Jessica Gronsbell, who is Assistant Professor in the Department of Statistical Sciences at the University of Toronto, as she draws reliable insights from imperfect electronic health records using a mix of classical statistical theory and modern machine learning tools.Her talk will primarily focus on the challenges in obtaining annotated outcome data from patient records and how leveraging unlabeled examples to improve model estimation and evaluation can reduce the annotation burden.You will be able to ask questions live!The session will be moderated by CANSSI Ontario Director and Department of Statistical Sciences Professor Dr. Lisa Strug.The Data Science Speaker Series at U of T (DSSS) is the result of a collaboration of Data Science programs at the University of Toronto: the Master of Science in Applied Computing (MScAC) in the Department of Computer Science, the Master of Management Analytics at the Rotman School of Management, and CANSSI Ontario.Together, we seek to advance knowledge in the field of data science by featuring world-class speakers from academic, healthcare, industry, finance, technology, sports, and other sectors and industries. Online (by Zoom) webpac.noreply@utoronto.ca