For questions about this event, please reach out to Veronica Lemme at lemmev@health.missouri.edu.

"Open Data, Machine Learning and Translational Neurotrauma" 

Presented by: Adam Ferguson, PhD, Director of Data Science in the Brain & Spinal Injury Center at Zuckerberg San Francisco General Hospital

Professor, Neurological Surgery, Weill Institute for Neuroscience at University of California San Francisco

Principal Investigator, San Francisco VA Healthcare System

Date: March 6, 2023, 4-5 p.m.

Description

Dr. Ferguson discussed the impact of open data sharing in the fields of traumatic brain injury (TBI) and spinal cord injury (SCI), and parallel innovations in machine learning/artificial intelligence (ML/AI) that are driving discovery, improving reproducibility and accelerating bench-to-bedside translation. He illustrated these points through a series of exemplar studies where advanced analytics such as ML/AI have been applied to open data pooled from numerous scientific laboratories to identify novel disease modifying factors that translated into the clinic to improve patient outcomes.

Speaker Bio

Adam R. Ferguson, MS, PhD is a professor of neurological surgery in the Weill Institute for Neurosciences at University of California San Francisco (UCSF), director of data science in the Brain and Spinal Injury at the Zuckerberg San Francisco General Hospital and principal investigator in the San Francisco VA Healthcare System. His research interests span from mechanistic neuroscience in model organisms to large-scale clinical data science and precision medicine research. He directs a diverse team of researchers performing a hybrid of bench neuroscience and translational data science, supported by grants from the NIH, VA, DoD, DARPA and nonprofits. He currently serves as vice president and president-elect of the National Neurotrauma Society. He is a founder and co-director of international data sharing efforts through the Open Data Commons for SCI (odc-sci.org) and TBI (odc-tbi.org) — federally supported data management ecosystems that enable FAIR data sharing, data publication and citation. He and his team have a history of harnessing advanced AI/ML tools to drive multi-modal biomarker discovery, bench-to-bedside translation and support precision therapeutics using pooled multicenter data. He has authored over 200 peer-reviewed papers across bench science, data science and clinical neurotrauma research.