UC San Francisco is upping its research into advanced computing in healthcare, launching an artificial intelligence center specifically to advance its use in medical imaging. The Center for Intelligent Imaging will develop and apply artificial intelligence in the quest to find new ways to use radiology to look inside the body and to evaluate health and disease. UCSF investigators in the center will work with Santa Clara, Calif-based NVIDIA, which develops AI products to support infrastructure and tools. The collaboration will aim to create new ways to enable the translation of AI into clinical practice. "Artificial intelligence represents the next frontier for diagnostic medicine," says Christopher Hess, MD, chair of UCSF's Department of Radiology and Biomedical Imaging.
The University of California, San Francisco is employing Nvidia technology to help develop artificial intelligence tools for clinical radiology. WHY IT MATTERS The two organizations will work together on several AI projects, including brain tumor segmentation, liver segmentation and clinical deployment, leveraging Nvidia's Clara healthcare toolkit and the tech giant's DGX-2 AI system. Clara Medical Imaging provides developers with the tools to build, manage and deploy intelligent imaging workflows and instruments, while Clara Genomics addresses the growing size and complexity of genomics sequencing and analysis with accelerated and intelligent computing. Powered by DGX software and the scalable architecture of Nvidia NVSwitch, the DGX-2 is a 2 petaFLOPS system combining 16 interconnected graphical processing units – the system could help UCSF researchers significantly cut the time to train AI models. The number of images acquired during common studies such as MRI and CT scans has swelled in recent years corresponding with the growing number of patients being imaged.
Clara Medical Imaging is a collection of developer toolkits built on NVIDIA's compute platform aimed at accelerating compute, artificial intelligence, and advanced visualization. Medical imaging industry is being transformed. A decade ago, the earliest applications to take advantage of GPU computing were image & signal processing applications. Today, GPUs are found in almost all imaging modalities, including CT, MRI, X-ray, and Ultrasound bringing more compute capabilities to the edge devices. Deep Learning research in Medical Imaging is also booming with more efficient and improved approaches being developed to enable AI-assisted workflows.Today, most of this AI research is being done in isolation and with limited datasets which may lead to overly simplified models.
Greg Zaharchuk, MD,PhD, is the co-founder of Subtle Medical and a professor of radiology and practicing neuroradiologist at Stanford University. He's an expert in advanced imaging methods, particularly applied to patients with neurological disease. Greg has received numerous awards and honors for his research and sits on several boards and advisory committees.
The Scripps Research Translational Institute is partnering with graphics firm NVIDIA to develop AI and deep learning best practices, tools and infrastructure to develop AI applications using genomic and digital health sensor data. With NVIDIA, California-based research organisation Scripps will establish a centre of excellence for artificial intelligence in genomics and digital sensors. Scripps and NVIDIA will work to advance the use of machine learning and deep learning to harness the exploding quantity of health data. The partnership will focus on data generated by faster, more affordable genome sequencing gear, and digital health sensors such as smartwatches, blood pressure cuffs and glucose monitors. NVIDIA AI experts and Scripps researchers and clinicians will use deep learning and machine learning, to tackle the deluge of genomics and sensor data.
Artificial intelligence (AI) can -- and already has -- improved the health outcomes of patients around the globe. Google earlier this month achieved 99 percent accuracy in metastatic breast care detection with an AI system, and Nvidia recently debuted a model that generates synthetic scans of brain cancer from whole cloth. Most deployments so far have been in isolation, though -- siloed in a way that prevents them coordinating with each other. That's what inspired Tatyana Kanzaveli, CEO of Silicon Valley startup Open Health Network and a cancer survivor, to forge a new path. The result -- PatientSphere -- launches broadly today.
Nvidia and the Scripps Research Translational Institute announced Tuesday that they're partnering to advance the use of artificial intelligence for early disease prediction and prevention. More specifically, they'll establish a center of excellence to accelerate the creation of AI applications that use genomic and digital health sensor data. So far, AI applications in medicine have largely focused on medical imaging, Kimberly Powell, vice president of healthcare at Nvidia, told reporters last week. While medical imaging is a powerful diagnostic tool, she said that AI needs to be applied to the medical data being collected from a growing number of sources. Data from DNA profiles or wearable technology, for instance, can go beyond diagnostics to help medical practitioners and researchers "think about the prevention of disease or the prediction of risk of disease in the first place."
Medical-related artificial intelligence could be the way of the future. The thought of high-tech devices tracking our health and giving us medical advice, diagnosing our condition or even performing certain medical tasks is scary to some but recently IEEE, the world's largest technical professional organization, conducted a survey about how millennial parents feel about how these issues affect their children and the result may shock you. Technology has continued to change the medical industry and the near future is no exception. What we have in our hospitals is simply amazing compared to what we had 100 years ago and 100 years from now medicine will no doubt be unrecognizable from what we have today. Change, however, can be a little scary at times.
Medical-related artificial intelligence could be the way of the future. The thought of high-tech devices tracking our health and giving us medical advice, diagnosing our condition or even performing certain medical tasks is scary to some but recently a company called IEEE conducted a survey about how millennial parents feel about how these issues affect their children and the result may shock you. Technology has continued to change the medical industry and the near future is no exception. What we have in our hospitals is simply amazing compared to what we had 100 years ago and 100 years from now medicine will no doubt be unrecognizable from what we have today. Change, however, can be a little scary at times.
In a report titled "The 5G Business Potential," networking and Telecommunications Company Ericsson has found wearable devices and artificial intelligence will improve resource efficiency and meet consumer demands for greater convenience and freedom of choice in the healthcare sector. The report analyzed the 5G business opportunity that comes from industrial digitalization in eight key global industries. Telecomm operators will have several areas to work on, such as hospital applications – virtual reality used in medical training, telemetry and online booking systems – and real-time medical data management. The area that has the most potential for operators addressing this industry with 5G, according to the report, is patient applications used outside of traditional hospital environments, such as precision medicine, online consultations and applications to monitor health and administer medication remotely to better manage chronic ailments. Forty-two percent of decision makers in the industry prefer 5G-enabled devices because they consume less power, according to the report.