250 Hutchison Rd, Rochester, NY 14620

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Join the Goergen Institute for Data Science for Improving Clinical Assessment During Pregnancy Using Imaging Analysis with Caitlin Dreisbach, PhD, RN, Assistant Professor at the University of Rochester School of Nursing.

Abstract: Biomedical images are collected by expert technicians but are prone to errors in interpretation because pattern recognition and estimation are challenging tasks. Convolutional neural networks, or algorithms that take images as input for both classification and regression problems, have been effective in clinical diagnostic, prognostic, and measurement using a wide range of imaging such as ultrasounds, X-ray, and magnetic resonance imaging. This talk will outline the potential for imaging analysis to transform clinical assessment during pregnancy, particularly for the estimation of fetal weight during the late third trimester.

Bio: Caitlin Dreisbach, PhD, RN, is an Assistant Professor at the University of Rochester School of Nursing with an affiliation in the Goergen Institute for Data Science. Dr. Dreisbach came to UR after completing a two-year postdoc at the Columbia University Data Science Institute. Her research focus is on the use of data science to make better clinical assessments during pregnancy. As a former labor and delivery nurse, Dreisbach is interested in reimagining the current state of technology use during labor and delivery. Dr. Dreisbach received her PhD and Master’s in Data Science (MSDS) from the University of Virginia, her Bachelor’s in Nursing (BSN) from The Johns Hopkins University, and a Bachelor’s of Science from Cornell University.

We are providing a Zoom option for this event. Please use the link below to enter the Zoom webinar.

Webinar link: https://rochester.zoom.us/j/91659929310

Webinar ID: 916 5992 9310

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