A consortium including the U.S. Department of Energy (DOE) and the University of California, San Francisco (UCSF) is working on a multiyear project to apply artificial intelligence (AI) for precision medicine to traumatic brain injury (TBI).
Several DOE national laboratories and UCSF are collaborating on the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) consortium. Using data deidentified from 3,000 TBI patients from TRACK-TBI, the Lawrence Livermore National Laboratory (LLNL), Lawrence Berkeley National Laboratory (LBNL), and Argonne National Laboratory (ANL) will employ AI techniques and DOE supercomputers to analyze CT and MRI studies, proteomic and genomic biomarkers, and clinical outcomes. These systems will be integrated into the DOE's research in science and energy, as well as national security programs.
"By harnessing subject-matter expertise across the participating universities and labs, and using next-generation artificial intelligence-based tool development for precision diagnostics, we are optimistic that we will be able to create clinically actionable information to guide personalized treatment for TBI patients," Dr. Geoff Manley, PhD, a professor of neurosurgery at UCSF, said in a statement.
The participating national laboratories will first seek to create a streamlined system for sharing this massive amount of research data among the laboratories. Next, they'll use the research data to develop a predictive model that could categorize or triage patients into risk categories and assess potential outcomes, according to the LLNL. The researchers also believe the project will serve in the long term as a proof of concept for a machine-learning model that could potentially also inform future models of diseases or disorders other than TBI.
The project began in March and is still in its initial stages. Teams at the DOE and USCF are continuing to work on the connectome -- a model of the structural connectivity of the human brain. Meanwhile, scientists at the LBNL and ANL are focusing on data analytics, including genetic information and CT scans of TBI patients, according to the LLNL.
