UC San Francisco’s Center for Digital Health Innovation and GE Healthcare have announced a partnership to develop a library of algorithms that will look to empower clinicians to make faster and more effective decisions.
The first wave of algorithms, which officials of the organizations said are “deep learning—complex problem-solving formulas—” aims to expedite differential diagnosis in acute situations such as trauma, to speed treatment, improve survival and reduce complications. These algorithms can be deployed worldwide via the GE Health Cloud and smart GE imaging machines, sharing the research of healthcare leaders with clinicians around the world who have varied expertise. They will aim to allow doctors to make better decisions about the diagnosis and management of patients with some of the most common and complex medical conditions.
Officials said the algorithms will be used to ensure providers around the world can access new knowledge and insights delivered through deep learning—a method by which machines can rapidly generate new levels of clinical and operational value from large imaging and textual data sets in ways that traditional machine learning methods cannot.
And, as algorithms are trained and the library of available algorithms expands, the associated applications will have the potential to do everything from predicting patient trajectories, to automating the triage of routine care, to improving process efficiency and enabling the development of more personalized therapies. By rapidly delivering information to clinicians about abnormalities, inefficiencies and personalized interventions, algorithms are designed to help providers improve diagnostic accuracy and patient outcomes, as well as improve clinical workflows and productivity, officials said.
One early example of an algorithm under development is a solution for pneumothorax, or a collapsed lung. The algorithm will be focused on teaching machines to distinguish between normal and abnormal scans so clinicians can prioritize and more quickly treat patients with pneumothorax, which can be a life-threatening condition.
Over the course of the partnership, GE Healthcare and UCSF will look to expand opportunities to integrate data not only from a variety of imaging technologies such as CT, MR and X-ray, but will also incorporate clinical data sets from the electronic health record (EHR) and other sources to enrich algorithm development and improve sensitivity, the organizations’ officials said.
“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,” Michael Blum, M.D., associate vice chancellor for informatics, director of CDHI and professor of medicine at UCSF, said in a statement. “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. Together, we will develop tools and algorithms that will allow clinicians and researchers to identify problems and ask questions that are only achievable with vast computing power and datasets.”
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