Digital Phenotyping with Wearables: Learning from Wearable Data to Predict Clinical Outcomes

October 27, 2020, 12:00 pm — 1:00 pm

Due to the COVID-19 outbreak, this seminar will be running via Zoom.

Zoom Meeting ID: 912 5563 9489

Zoom Meeting Passcode: 692356

Join Zoom Meeting: https://wustl-hipaa.zoom.us/j/91255639489?pwd=ODZ4TTNFcEJFNVl0Rmw3S09HaDl1UT09

The Institute for Informatics and the Division of Pulmonary and Critical Care Medicine are pleased to announce our inaugural Symposium for Artificial Intelligence in Medicine (SAIM) seminar series. This symposium is designed to be a forum for the discussion of revolutionary healthcare technologies and the ongoing development of innovative healthcare technologies across our campuses, with the goal of uniting people with similar interests and fostering collaboration and growth. We welcome clinicians and trainees from all backgrounds and at all levels who are interested in learning more about translational artificial intelligence, machine learning and healthcare information technology. This year, our second seminar will be delivered by Dr. Chenyang Lu, on October 27, 2020.

Chenyang Lu is the Fullgraf Professor at Washington University in St. Louis. He has worked extensively in the area of mobile health and clinical machine learning for the past decade, specializing in developing software infrastructure and analytical models for predicting clinical outcomes using data collected through wearable sensors and electronic health records. The author and co-author of over 200 research papers with over 22,000 citations and an h-index of 70, Professor Lu served as Editor-in-Chief of ACM Transactions on Sensor Networks from 2011 to 2017 and Chair of the IEEE Technical Committee on Real-Time Systems (TCRTS) from 2018 to 2019. He is a Fellow of IEEE.

Please contact Becky Light, light@wustl.edu, with any questions.