NVIDIA WEBINAR
To build robust AI algorithms, hospitals often need to share and combine their local knowledge, but do so without compromising privacy. Federated learning on NVIDIA Clara Train 3.1 makes this possible.
In this webinar, learn how Clara Train 3.1 features enterprise-grade, secure federated learning for healthcare organizations and enables:
Dive into these great new features and how Clara Train 3.1 was used to build EXAM, an AI model built by 20 hospitals in 20 days to predict COVID-19 patient oxygen needs.
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"Holger Roth is a Sr. Applied Research Scientist at NVIDIA focusing on deep learning for medical imaging. He has been working closely with clinicians and academics over the past several years to develop deep learning based medical image computing and computer-aided detection models for radiological applications. He is an Associate Editor for IEEE Transactions of Medical Imaging and holds a Ph.D. from University College London, UK. In 2018, he was awarded the MICCAI Young Scientist Publication Impact Award. Personal webpage: https://www.holgerroth.com/"
"Kris Kersten is a Solution Architect at NVIDIA focused on AI, working to scale ML and DL solutions to solve today's most pressing problems in Healthcare. Prior to NVIDIA, Kris worked at Cray Supercomputers studying hardware and software performance characteristics from low-level cache benchmarking to large-scale parallel simulation. "
Raghav Mani is the Product Manager for Healthcare AI at NVIDIA and is focused on building tools for medical imaging researchers and developers of Smart Hospital applications. Prior to NVIDIA, Raghav worked at Epic, where he led different product & engineering teams including their Deep Learning team and their patient engagement platform called MyChart. He holds a bachelor’s degree from Indian Institute of Technology in Madras and a master's degree from Texas A&M University.
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Date & Time: Wednesday, April 22, 2018