BIDS-BCHSI Research Xchange Forum
Using Biomedical Knowledge Graphs for Medical Diagnosis Prediction
Date: Monday, February 1, 2021
Time: 12:30-1:30 PM Pacific Time
Location: Virtual Participation
Using Biomedical Knowledge Graphs for Medical Diagnosis Prediction
Speaker: Lowry Kirkby, PhD, Data Science Health Innovation Fellow
The BIDS-BCHSI Research Xchange Forum is an open discussion platform for the interdisciplinary exchange of ideas and research projects at the intersection of healthcare and data science. Participants are invited to engage in a variety of activities, including presentations of work-in-progress, discussions and critiques of recent papers and AI methods in healthcare, introductions to new tools and methods, and opportunities to foster new collaborations. Invited speakers include leading voices in AI and Healthcare, and active conversations invite participants to share fresh perspectives. Clinicians and physicians with an interest in data science methods and tools, as well as data science faculty and researchers with applications or interests in the healthcare and health sciences, are welcome and encouraged to participate. Regular participants will also include the I4H Fellows, as well as post-docs, staff, and faculty from UC Berkeley, UCSF, and Johnson & Johnson. The immediate goals of this Forum are to share our current research projects with a wider audience, and to increase engagement and improve communication among the three host organizations. Meetings are held virtually on the first Monday of each month at 12:30-1:30 PM Pacific Time, and interested members of the UC Berkeley, UCSF, and Johnson & Johnson communities are invited to use this registration form to receive the schedule and access links. Please contact InnovateForHealth@berkeley.edu for more information.
Speaker(s)
Lowry Kirkby
Lowry Kirkby, now a computational neuroscientist with Rune Labs, joined BIDS and BCHSI/UCSF in Fall 2019 as part of the first cohort of Data Science Health Innovation Fellows in the Innovate For Health program. She obtained her undergraduate degree in Physics from the University of Oxford, and her PhD in Biophysics from the University of California, Berkeley. She completed her postdoctoral research in Neuroscience at the University of California, San Francisco, where she studied large-scale electrical recordings of the human brain to understand how neural circuits are altered in depression and anxiety.