UCSF to Develop Machine Learning for CDS, Imaging Analytics
November 18, 2016 - The University of California San Francisco’s Center for Digital Health Innovation (CDHI) and GE Healthcare are partnering to develop a cache of machine learning algorithms and imaging analytics tools that can be used to provide clinical decision support for patients with complex medical needs.
The collaboration will initially focus on creating tools to speed accurate differential diagnoses for trauma patients before branching out into predictive analytics, precision medicine, and increased automation of routine care.
“With this partnership, we have the opportunity to leverage the technical expertise of one of the largest providers of medical technology globally and the clinical and research expertise of UCSF, one of the largest recipients of National Institutes of Health (NIH) funding, in order to make the promise of precision healthcare a reality,” said Michael Blum, MD, associate vice chancellor for informatics, director of CDHI, and professor of medicine at UCSF.
“Next generation data science techniques have already transformed the industrial and consumer world. With this collaboration, these technologies will be applied to our clinical data and images to provide clinicians with actionable information in near real-time.”