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Meant to optimize diagnosis and treatment, they can be deployed worldwide via GE's Health Cloud and smart imaging machines.
November 22, 2016
By: Laura Kurtzman
University of California - San Francisco
UC San Francisco’s Center for Digital Health Innovation and GE Healthcare have announced a partnership to develop a library of deep learning algorithms—complex problem-solving formulas—that will empower clinicians to make faster and more effective decisions about the diagnosis and management of patients with some of the most common and complex medical conditions. The first wave of algorithms 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 health care leaders with clinicians around the world who have varied expertise. 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. “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. 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.” 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. Deep learning makes achieving these healthcare outcomes possible, and the partnership enables all products to be developed in tandem with providers to enhance patient safety and the patient experience. “This partnership is about the future of healthcare—technology, analytics and cloud computing power all combining to enable clinicians to make faster decisions for better patient outcomes,” said John Flannery, president and CEO of GE Healthcare. “By working hand-in-hand with a leading academic medical center like UCSF to design, build and verify new deep learning tools, we are defining how digital health solutions can be seamlessly integrated into care.” The collaboration is initially focused on high-volume, high-impact imaging to create algorithms that reliably distinguish between what is considered a normal result and what requires follow up or acute intervention. 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. “What is so powerful about combining analytics, deep learning, and cloud technology is that the solutions will only get smarter and more scalable over time,” said Charles Koontz, Chief Digital Officer of GE Healthcare. “While this partnership combines the capabilities of a large medical technology vendor and a major research institution conveniently located near Silicon Valley, it’s the global users of the algorithms who will disrupt the way care is delivered by leveraging the tools we have developed. Patients who previously lacked even the most basic medical services may benefit from GE Healthcare’s best-in-class technology and UCSF’s world renowned clinical expertise.” Over the course of the partnership, GE Healthcare and UCSF will 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 and other sources to enrich algorithm development and improve sensitivity. GE Health Cloud will enable the solutions and insights to become smarter, more robust and more widely accessible over time.
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