Computer Vision / Video Analytics

Healthcare – Top Resources from GTC 21

Here are the latest resources and news for healthcare developers from GTC 21, including demos and specialized sessions for building AI in drug discovery, medical imaging, genomics, and smart hospitals. Learn about new features now available in NVIDIA Clara Train 4.0, an application framework for medical imaging that includes pre-trained models, AI-assisted annotation, AutoML, and federated learning.

The developer resources listed below are exclusively available to NVIDIA Developer Program members. Join today for free in order to get access to the tools and training necessary to build on NVIDIA’s technology platform here.

On-Demand Sessions

Accelerating Drug Discovery with Advanced Computational Modeling
Speaker: Robert Abel, Executive Vice President, Chief Computational Scientist, Schrödinger

Learn about how integrated deployment and collaborative use of advanced computational modeling and next-generation machine learning can accelerate drug discovery from Robert Abel, Executive Vice President, Chief Computational Scientist at Schrödinger.

Using Ethernet to Stream Medical Sensor Data
Speaker: Mathias Blake, Platform Architect for Medical Devices, NVIDIA

Explore three technologies from NVIDIA that make streaming high-throughput medical sensor data over Ethernet easy and efficient—NVIDIA Networking ConnectX NICs, Rivermax SDK with GPUDirect, and Clara AGX. Learn about the capabilities of each of these technologies and explore examples of how these technologies can be leveraged by several different types of medical devices.

Automate 3D Medical Imaging Segmentation with AutoML and Neural Architecture Search
Speaker: Dong Yang, Applied Research Scientist, NVIDIA

Recently, neural architecture search (NAS) has been applied to automatically search high-performance networks for medical image segmentation. Hear from NVIDIA Applied Research Scientist, Dong Yang, to learn about AutoML and NAS techniques in the Clara Train SDK.

Deep Learning and Accelerated Computing for Single-Cell Genomic Data
Speaker: Avantika Lal, Sr. Scientist in Deep Learning and Genomics, NVIDIA

Learn about accelerating discovery of cell types in the human body with RAPIDS and AtacWorks, a deep learning toolkit to enhance ATAC-seq data and identify active regulatory DNA more accurately than existing state-of-the-art methods.


Creating Medical Imaging Models with Clara Train 4.0
Learn about the upcoming release of NVIDIA Clara Train 4.0, including infrastructure upgrades based on MONAI, expansion into digital pathology, and updates to DeepGrow for annotating organs effectively in 3D images.


Accelerating Drug Discovery with Clara Discovery’s MegaMolBart
See how NVIDIA Clara Discovery’s MegaMolBart, a transformer-based NLP model developed with AstraZeneca, trained on millions of molecules, can accelerate the drug discovery process.

NVIDIA Triton Inference Server: Generative Chemical Structures
Watch NVIDIA Triton Inference Server power deep learning models to propose thousands of molecules per second for drug design that can be further refined with physics-based simulations.

Visit NVIDIA On-Demand to explore the extensive catalog of sessions, podcasts, demos, research posters and more.

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