Developer Resources for Healthcare
A Hub of News, SDKs, Technical Resources, and More for Developers Working in Healthcare.
Application Frameworks
NVIDIA Clara Imaging
NVIDIA Clara™ Imaging is an application framework that accelerates the development and deployment of AI in medical imaging. Clara Imaging offers easy-to-use, domain-optimized tools to create high-quality, labeled datasets, collaborative techniques to train robust AI models, and end-to-end software for scalable and modular AI deployments.
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NVIDIA Clara Parabricks
NVIDIA Clara™ Parabricks is a computational framework supporting genomics applications from DNA to RNA. It employs NVIDIA’s CUDA, HPC, AI, and data analytics stacks to build GPU accelerated libraries, pipelines, and reference application workflows for primary, secondary, and tertiary analysis.
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NVIDIA Clara Guardian
NVIDIA Clara™ Guardian enables AI application developers to develop and deploy smart sensors with multimodal AI anywhere in the hospital. Access healthcare specific pre-trained models, intelligent video analytics powered by NVIDIA DeepStream, and automatic speech recognition and natural language processing solutions powered by NVIDIA Jarvis conversational AI software.
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Over 150 healthcare sessions covering AI and HPC in drug discovery, genomics, medical imaging, software-defined instruments, and more. April 12-16.
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AutoML-Enabled AI Model Training
Read the latest release of Clara Train v3.0 introducing the AutoML module, making the process of hyper-parameter tuning seamless by intelligently searching for the optimal parameter settings to train models automatically.
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Deploying Healthcare AI Workflows
The Clara Deploy Application Framework allows you to ingest massive amounts of data from popular data sources like PACS (using a DICOM adapter), encapsulate your medical imaging business logic on operators (i.e. image segmentation) as part of a pipeline, and execute those jobs at scale using cloud-native paradigms based on containers and Kubernetes orchestration.
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Faster Development of Speech Models
Neural Modules is a new open source toolkit that makes it possible to easily and safely compose complex neural network architectures using reusable components. Neural Modules is also built for speed and can scale out training to multiple GPUs and multiple nodes.
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Deploying Clara Train with AWS Quick Start
Get an overview of the NVIDIA Clara Train SDK for medical imaging, and demonstrate how it can be easily deployed on the AWS Cloud using the published Quick Start.
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GPU-Accelerated Biomolecular Simulations and AI-Powered Chemistry
In this session, learn how GPU-accelerated biomolecular simulation and machine learning are being used by scientists in the fight against COVID-19.
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Building Smart Hospitals to Fight COVID-19
Learn how to use Clara Guardian to develop and deploy smart sensors with multimodal AI anywhere in a healthcare facility.
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NVIDIA Clara Parabricks
Discuss features of the NVIDIA Clara Parabricks application framework.
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Data Augmentation and Segmentation with Generative Networks for Medical Imaging
A generative adversarial network (GAN) is a pair of deep neural networks: a generator that creates new examples based on the training data provided and a discriminator that attempts to distinguish between genuine and simulated data. As both networks improve together, the examples created become increasingly realistic. This technology is promising for healthcare, because it can augment smaller datasets for training of traditional networks.
Medical Image Classification Using the
MedNIST Dataset
Explore an introduction to deep learning for radiology and medical imaging by applying CNNs to classify images in a medical imaging dataset.
Find Your Application-Specific Resource
cuDNN
The NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers.
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TensorRT
NVIDIA® TensorRT™ is an open-source platform for high-performance deep learning inference, which includes an inference optimizer and runtime that delivers low latency and high throughput for your healthcare applications.
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DALI
The NVIDIA Data Loading Library (NVIDIA DALI®) is a portable, open-source library for decoding and augmenting images and videos to accelerate deep learning applications in healthcare. DALI reduces latency and training time, mitigating bottlenecks, by overlapping training and pre-processing.
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TensorRT Inference Server
NVIDIA TensorRT Inference Server deploys and scales AI models in data center production. It maximizes GPU utilization and supports all major AI models and frameworks for healthcare.
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Jetpack
The NVIDIA Jetpack™ SDK is the most comprehensive solution for building AI applications. The latest release supports NVIDIA Jetson AGX Xavier™, Jetson™ TX2, Jetson TX1, and Jetson Nano.
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Automatic Mixed Precision
Deep neural network training has traditionally relied on IEEE single-precision format; however with mixed precision, you can train with half precision while maintaining the network accuracy achieved with single precision. This technique of using both single and half-precision representations is referred to as mixed-precision technique and is used by leading institutions such as Nuance.
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IndeX
NVIDIA IndeX™ is a commercial 3D volumetric visualization SDK that allows scientists and researchers to visualize and interact with massive datasets, make real-time modifications, and navigate to the most pertinent parts of the data, all in real time, to gather better insights faster.
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OptiX
The NVIDIA OptiX™ API is an application framework for achieving optimal ray-tracing performance on the GPU. It provides a simple, recursive, and flexible pipeline for accelerating ray tracing algorithms.
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NVIDIA Nsight Graphics
NVIDIA Nsight™ Graphics is a standalone developer tool that enables you to debug, profile, and export frames built with Direct3D (11, 12, DXR), Vulkan (1.1, NV Vulkan Ray Tracing Extension), OpenGL, OpenVR, and the Oculus SDK.
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GRID
NVIDIA GRID® Virtual PC (GRID vPC) and Virtual Apps (GRID vApps) are virtualization solutions that deliver a user experience that’s nearly indistinguishable from a native PC. With server-side graphics and comprehensive management and monitoring capabilities, GRID future-proofs your virtual desktop infrastructure (VDI) environment.
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vGPU
NVIDIA virtual GPU (vGPU) technology uses the power of NVIDIA GPUs and NVIDIA virtual GPU software products to offer a consistent user experience for every virtual workflow.
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NVIDIA Quadro Virtual Workstation
With workloads becoming increasingly compute-intensive and a constantly growing need for mobility and collaboration, more workloads are being migrated to the cloud. Cloud-based workstations, paired with traditional on-premises infrastructure, give an enterprise the flexibility and business agility to stay competitive.
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NGC
NGC is the hub for GPU-optimized software for deep learning, machine learning, and high-performance computing (HPC) that takes care of all the plumbing so data scientists, developers, and researchers can focus on building solutions and gathering insights.
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CUDA Toolkit
The NVIDIA CUDA Toolkit provides a development environment for creating high-performance GPU-accelerated applications. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms, and HPC supercomputers.
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RAPIDS
The RAPIDS suite of open-source software libraries and APIs gives you the ability to execute end-to-end data science and analytics pipelines entirely on GPUs.
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PROGRAMS FOR YOU
Developer Resources
The NVIDIA Developer Program provides the advanced tools and training needed to successfully build applications on all NVIDIA technology platforms. This includes access to hundreds of SDKs, a network of like-minded developers through our community forums, and more.
Technical Training
NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI, accelerated computing, and accelerated data science to solve real-world problems. Powered by GPUs in the cloud, training is available as self-paced, online courses or live, instructor-led workshops.
Accelerate Your Startup
NVIDIA Inception—an acceleration platform for AI, data science, and HPC startups—supports over 7,000 startups worldwide with go-to-market support, expertise, and technology. Startups get access to training through the DLI, preferred pricing on hardware, and invitations to exclusive networking events.
NVIDIA Healthcare News
Creating Medical Imaging Models with NVIDIA Clara Train 4.0
NVIDIA Clara Train, an application framework for training medical imaging models, has undergone significant changes for its upcoming release at the beginning of May, with product enhancements for better AI model training.
NIH, NVIDIA Use AI to Trace COVID-19 Disease Progression in Chest CT Images
Researchers from the U.S. National Institutes of Health have collaborated with NVIDIA experts on an AI-accelerated method to monitor COVID-19 disease severity over time from patient chest CT scans.
NVIDIA Clara Imaging Brings AI-Assisted Annotation and Model Training to XNAT to Enable Medical Imaging AI
Building on the announcement at RSNA 2019, XNAT, the most widely-used open-source informatics platform for imaging research, announced the beta release of XNAT Machine Learning (XNAT ML).
New on NGC Catalog: Samsung SDS Brightics, an AI Accelerator for Automating and Accelerating Deep Learning Training
The Kubernetes-based, containerized application, is now available on the NVIDIA NGC Catalog – a GPU-optimized hub for AI and HPC containers.
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