Edge computing makes it possible for every hospital device to become #AI enabled. Along these lines, today NVIDIA unveiled Clara Federated Learning, a reference application for distributed, collaborative AI model training that preserves patient privacy. Running on NVIDIA NGC-Ready for Edge servers from global system manufacturers, these distributed client systems can perform deep learning training locally and collaborate to train a more accurate global model.
NVIDIA Clara FL uses distributed training across multiple hospitals to develop robust AI models without sharing patient data. It runs on the recently announced NVIDIA EGX intelligent edge computing platform, which securely provisions the federated server and the collaborating clients, delivering everything required to begin a federated learning project, including application containers and the initial AI model.
Healthcare giants around the world are pioneering the technology with the aim to develop personalized AI for their doctors, patients and facilities where medical data, applications and devices are on the rise and patient privacy must be preserved:
- ACR is piloting NVIDIA Clara FL in its AI-LAB, a national platform for medical imaging. The AI-LAB will allow the ACR’s 38,000 medical imaging members to securely build, share, adapt and validate AI models. Healthcare providers that want access to the AI-LAB can choose a variety of NVIDIA NGC-Ready for Edge systems, including from Dell, Hewlett Packard Enterprise, Lenovo and Supermicro.
- UCLA Radiology is also using NVIDIA Clara FL to bring the power of AI to its radiology department. As a top academic medical center, UCLA can validate the effectiveness of Clara FL and extend it in the future across the broader University of California system.
- Partners HealthCare in New England also announced a new initiative using NVIDIA Clara FL. Massachusetts General Hospital and Brigham and Women’s Hospital’s Center for Clinical Data Science will spearhead the work, leveraging data assets and clinical expertise of the Partners HealthCare system.
- In the U.K., NVIDIA is partnering with King’s College London and Owkin to create a federated learning platform for the National Health Service. The Owkin Connect platform running on NVIDIA Clara enables algorithms to travel from one hospital to another, training on local datasets. It provides each hospital a blockchain-distributed ledger that captures and traces all data used for model training.
- The project is initially connecting four of London’s premier teaching hospitals, offering AI services to accelerate work in areas such as cancer, heart failure and neurodegenerative disease, and will expand to at least 12 U.K. hospitals in 2020.
Making Everything Smart in the Hospital with NVIDIA Clara AGX
With the rapid proliferation of sensors, medical centers like Stanford Hospital are working to make every system smart. To make sensors intelligent, devices need a powerful, low-power AI computer. To help meet this challenge, the new NVIDIA Clara AGX is an embedded AI developer kit that can handle image and video processing at high data rates, bringing AI inference and 3D visualization to the point of care.
Hyperfine’s mobile MRI system uses an NVIDIA GPU.
NVIDIA Clara AGX scales from small, embedded devices to sidecar systems to full-size servers. Clara AGX is powered by NVIDIA Xavier SoCs, the same processors that control self-driving cars. They consume as little as 10W, making them suitable for embedding inside a medical instrument or running in a small adjacent system.
A perfect showcase of Clara AGX is Hyperfine, the world’s first portable point-of-care MRI system. The revolutionary Hyperfine system will be on display in NVIDIA’s booth at this week’s RSNA event. Hyperfine’s system is among the first of many medical instruments, surgical suites, patient monitoring devices and smart medical cameras expected to use Clara AGX. We’re witnessing the beginning of an AI-enabled internet of medical things.
