Nvidia Corp. wants to make artificial intelligence a staple of the healthcare industry with a new distributed learning technique announced today that can train machine learning models while protecting patient privacy.

AI holds great promise, but for industries such as healthcare where data privacy is of paramount importance, tapping into that potential is a big challenge. The problem is that any data that might be useful to train models is almost always confidential, which means it can’t be shared with technology partners.

Nvidia reckons it can solve this problem with its new Clara Federated Learning technique, which ensures that patient data remains within healthcare providers’ systems at all times.

Clara FL is a reference application for distributed AI training that’s designed to run on Nvidia’s recently announced EGX intelligent edge computing platform. Those systems are capable of performing deep learning training locally at the “network edge,” where the data resides, without moving it.

Clara FL is also collaborative, which means multiple systems can work together at different locations to create more accurate, global models, Nvidia Vice President of Healthcare Kimberly Powell said in a blog post.

Clara FL has already been put to use by radiologists at several top healthcare providers, including the American College of Radiology, King’s College London and UCLA Health. First, the radiologists label their data using the NVIDIA Clara AI-Assisted Annotation software development kit, which is integrated with medical viewers such as 3D slicer, MITK, Fovia and Philips Intellispace Discovery.

“Using pre-trained models and transfer learning techniques, NVIDIA AI assists radiologists in labeling, reducing the time for complex 3D studies from hours to minutes,” Powell said.

The models are then trained on Nvidia’s servers located on site and the results are shared over a secure link back to the federated learning center. Only those results are shared, with the patient data remaining where it is, ensuring it remains secure.

“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,” Powell wrote. “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.”

Alongside Clara FL, Nvidia announced a new embedded AI developer kit called Clara AGX that can handle image and video processing at very high data rates, enabling AI inference and 3D visualization capabilities to be embedded in medical devices.

Nvidia AGX is powered by the company’s low-powered Xavier systems-on-a-chip, which are tiny processors typically used to power self-driving cars. The software has already been embedded in portable “Hyperfine” magnetic resonance imaging devices for early tests, and Nvidia said it can also be used with various other medical instruments, surgical suites, smart medical cameras and patient monitoring devices.

“We’re witnessing the beginning of an AI-enabled internet of medical things,” Powell said.

Nvidia said the Clara AGX SDK will be made available soon to early-access users.

Image: Nvidia