NVIDIA Clara
NVIDIA® Clara™ is a platform of AI applications and accelerated frameworks for healthcare developers, researchers, and medical device makers creating AI solutions to improve healthcare delivery and accelerate drug discovery. Clara’s domain-specific tools, AI pre-trained models, and accelerated applications are enabling AI breakthroughs in numerous fields, including genomics, natural language processing (NLP), imaging, medical devices, drug discovery, and smart hospitals.
Documentation Center
04/27/23
NVIDIA Holoscan is a hybrid computing platform that combines hardware systems for low-latency sensor and network connectivity, optimized libraries for data processing and AI, and core microservices to run surgical video, ultrasound, medical imaging, and other applications anywhere, from embedded to edge to cloud.
Documentation Center
04/28/23
Clara Parabricks is a complete software solution for next-generation sequencing, including short- and long-read applications, supporting workflows that start with basecalling and extend through tertiary analysis. Clara Parabricks Pipelines were built to optimize acceleration, accuracy, and scalability. Users can achieve a 35-50X acceleration and 99.99 percent accuracy for variant calling when comparing against CPU-only BWA-GATK4 pipelines. It can run the full GATK4 Best Practices and is also fully configurable, letting users choose which steps, parameter settings, and versions of the pipeline to run.
Documentation Center
03/02/23
NVIDIA Clara Viz is a platform for visualization of 2D/3D medical imaging data. The core of this platform is the Clara Viz SDK, which is designed to enable developers to incorporate high performance volumetric visualization of medical images in applications with an easy-to-use API.
Documentation Center
04/25/23
The MONAI framework is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm.
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