With over 100 exhibitors at the annual Radiological Society of North America conference using NVIDIA technology to bring AI to radiology, 2019 looks to be a tipping point for AI in healthcare. Despite AI's great potential, a key challenge remains: gaining access to the huge volumes of data required to train AI models while protecting patient privacy. Partnering with the industry, we've created a solution. Today at RSNA, we're introducing NVIDIA Clara Federated Learning, which takes advantage of a distributed, collaborative learning technique that keeps patient data where it belongs -- inside the walls of a healthcare provider. Clara Federated Learning (Clara FL) runs on our recently announced NVIDIA EGX intelligent edge computing platform.

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.