By partnering with leading healthcare institutions and organizations like the American College of Radiology, GE Healthcare and Nuance, NVIDIA will help bring to market new solutions that transform healthcare.
At the annual meeting of the Radiological Society of North America (RSNA) in Chicago, attended by more than 50,000 professionals, NVIDIA announced partnerships with two leading healthcare-solution providers — GE Healthcare and Nuance — that will use NVIDIA’s deep learning platform to bring AI to medical imaging.
GE Healthcare will bring NVIDIA’s AI computing platform to GE Healthcare’s 500,000 imaging devices globally — the partnership will deliver the new NVIDIA-accelerated Revolution Frontier CT, which is two times faster in imaging processing than its predecessor.
The second partnership with Nuance aims to bring machine learning to radiologists and data scientists across the entire healthcare system. Nuance is announcing its new AI Marketplace for Diagnostic Imaging, built on NVIDIA’s deep learning platform which will allow radiologists to get involved in the creation of algorithms that can then be made readily available in the clinic.
In addition to our booth at RSNA, we’ve organized several special activities.
We’ll provide the first hands-on training in deep learning at the show, using certified instructors from our Deep Learning Institute (DLI). The RSNA Deep Learning Classroom conducted by the DLI will present a range of hands-on courses for more than 1,000 attendees to help them understand deep learning tools, write algorithms and improve their understanding of AI technology.
In the show’s first ever Machine Learning Pavilion, NVIDIA will showcase AI demos. To see them, visit us in the North Hall 3, booth 8543.
To increase speed and access to better quality care through medical imaging, NVIDIA will host partners at the booth to collaborate on medical image challenges with AI. Partners include Massachusetts General Hospital and 16 bit.
Kimberly Powell, VP of Healthcare at NVIDIA, will present a talk on “Intelligent Machines, Empowered Radiologists, Efficient Hospitals” on Tuesday, Nov. 28, from 12:30-12:50 pm at the Machine Learning Theater (ML33 Machine Learning Showcase North Hall).