Advance Medicine and Research with AI

Healthcare demands new computing paradigms to meet the need for personalized medicine, next-generation clinics, enhanced quality of care, and breakthroughs in biomedical research to treat disease. With NVIDIA, healthcare institutions can harness the power of artificial intelligence and high-performance computing (HPC) to define the future of medicine.

Latest Healthcare News

Clara Holoscan MGX
Image credit: Tim Ainsworth/UK Biobank

NVIDIA Launches Platform for Medical Devices and Computational Sensing Systems

NVIDIA Clara Holoscan MGX expands the Clara Holoscan platform to provide an all-in-one, medical-grade reference architecture, as well as long-term software support to accelerate innovation in the medical device industry.

Digital Biology Breakthroughs on Cambridge-1

Startups Harness Cambridge-1 to Power Digital Biology Breakthroughs

Select NVIDIA Inception members are advancing drug discovery, researching antibody response, creating AI-powered decision-making systems for vaccine development, and mapping the causes of disease with recommender systems.

UF Health and NVIDIA Build World's Largest Clinical Language Generator

UF Health and NVIDIA Build World's Largest Clinical Language Generator

Trained on a decade of data representing some 3 million patients, SynGatorTron is a language model that can create synthetic patient profiles. Researchers plan to use SynGatorTron to develop better AI for rare disease research and clinical trials, as well as to reduce data set bias.

The World's Brightest Minds. One Unique Event.

Conference & Training March 21 - 24

AI is creating new possibilities in healthcare. Advances in computational biology are accelerating every phase of drug discovery, a new generation of software-defined medical devices are enabling real-time sensing, smart hospitals are improving clinical experiences, and accelerated computing is unlocking the human genome to enable better precision medicine. Get the latest innovations across healthcare at GTC22.

  • Accelerating Healthcare Innovation with AI

    • Kimberly Powell, Vice President of Healthcare, NVIDIA

    Hospitals, operating rooms, genomic sequencing centers, and pharmaceutical companies generate massive amounts of data, creating the opportunity to build AI models, platforms, and robotic systems that can predict, comprehend, learn, and act. Get the latest on how life science researchers, developers, and medical device makers are using NVIDIA Clara™ to invent breakthroughs in healthcare delivery and drug discovery.

  • Accelerating Drug Design With AI

    • Ola Engkvist, Head of Molecular AI, AstraZeneca

    Artificial intelligence has become impactful during the last few years in chemistry and the life sciences, pushing scientific boundaries forward as exemplified by the recent success of AlphaFold2. In this presentation, I’ll provide an overview of how AI has impacted drug design in the last few years, where we are now, and what progress we can reasonably expect in the coming years. The presentation will have a focus on deep learning-based molecular de novo design; however, aspects of synthesis prediction, molecular property predictions, and chemistry automation will also be covered.

  • Capitalizing on the Metaverse of Medical Imaging Data to Improve AI Performance

    • Caroline Chung, Chief Data Officer, MD Anderson Cancer Center

    With the exponential growth in volume of medical imaging data, the mounting need for AI to help clinical teams handle and optimally use all the available imaging is apparent. However, developing AI tools that have successfully been translated into the clinical setting has been relatively slow and cautious. Challenges faced in development and clinical adoption may have solutions that lie within the imaging-associated metadata, as the impact of factors such as image quality and generalizability of AI models may be reflected in the rich contextual information that surrounds an imaging exam.

  • When Every Second Counts: Accelerated Genome Sequencing for Critical Care

    • Euan Ashley, Professor of Medicine and Genetics, Stanford University

    This session will look at how a collaborative team recently set the Guinness World Record for the fastest DNA sequencing technique while making medical diagnoses in under eight hours from whole genome sequencing in critical care patients at Stanford hospitals. We’ll explore how something that used to take years and cost millions of dollars can now be realized in hours in modern hospital settings and outline the computational and algorithmic infrastructure that supported the advance.

  • OpenFold: Democratizing Access to Predicting and Modeling Protein Structures

    • Mohammed AlQuraishi, Professor, Columbia University

    Deep learning methods that predict structures with accuracy rivaling experimental methods have revolutionized protein structure prediction. Such methods require substantial amounts of compute to train, however, and code and data infrastructure to learn new models tailored to new tasks.

    In this session, learn about OpenFold, a new open-source platform for training leading protein structure prediction models. OpenFold provides the code and data necessary to train new models from scratch, as well as pr-trained models under a permissive license for broad use by academia and industry.

Healthcare luminaries at GTC 22

Impulsionando Soluções da Área da Saúde com Computação Acelerada

Drug Discovery

With accelerated computing, researchers can virtually model millions of molecules and screen hundreds of potential drugs at a time, reducing costs and speeding time to solution.


Using HPC to accelerate genome analysis in population and cancer genomic studies can help identify rare diseases and bring tailored therapeutics to market faster, advancing the journey to precision medicine.

Medical Imaging

AI-powered tools can be an extra set of “eyes,” helping clinicians to quickly read images, calculate measurements, monitor changes, and identify urgent findings to optimize workflows and enhance patient care.

Smart Hospitals and Medical Instruments

From smart sensors to medical instruments that support real-time, advanced image processing, AI at the edge can deliver immediate insights, optimizing patient care and realizing the promise of smart hospitals.

Cambridge-1: Acelerando a Pesquisa na Área da Saúde

O Cambridge-1 é o primeiro supercomputador da NVIDIA dedicado ao desenvolvimento da biologia digital, da genômica, da computação quântica e da pesquisa em AI no Reino Unido. Ele capacita os principais cientistas e pesquisadores britânicos para colaborar em pesquisas inovadoras.

Startups Revolucionárias da Área da Saúde de AI

As startups de AI da área da saúde são essenciais para expandir os limites da inovação na saúde. O NVIDIA Inception promove mais de mil startups nesta área, desenvolvendo ferramentas de ponta baseadas em GPU para otimizar as operações, aprimorar o diagnóstico e elevar o atendimento ao paciente. Saiba mais sobre a revolucionária tecnologia sendo desenvolvida por startups da área da saúde clicando nos logos abaixo.

Taking AI to Market

Taking AI to Market

With another $28 million in recent funding, Arterys will further develop their ecosystem of partners and clinical-grade AI solutions on their AI web platform, Arterys Marketplace, bridging the gap between medical researchers and clinicians.

Startup’s Sensors Keep Hospitals Safe

Sensores de Startup Mantêm os Hospitais Seguros

Com 800 câmeras com GPU implementadas nos 10 hospitais da Northwestern, a Artisight ajuda a equipe do hospital na condução de triagens térmicas remotas, limitando a exposição da equipe à COVID-19.

AI Helps Triage Patients with COVID-19 Symptoms

AI Helps Triage Patients with COVID-19 Symptoms

AI startup Lunit and their CE-marked solution, Lunit INSIGHT CXR, uses AI to quickly detect 10 different radiological findings on chest x-rays, including pneumonia, often present in COVID-19 patients, and potentially cancerous lung nodules in seconds.

Computação da Área da Saúde do Data Center para o Edge e o Cloud

Powerful Computing for Data Centers

Powerful Computing for Data Centers

Built with NVIDIA A100 Tensor Core GPUs, NVIDIA DGX™ A100 delivers unprecedented compute performance to aid the discovery of new drugs, uncover genetic mutations to better fight disease, and drive healthcare innovation. Combined with access to experts and easy-to-deploy infrastructure, NVIDIA DGX A100 is the foundational building block in constructing AI data centers.

 Watch Webinar: DGX A100—The Universal AI System for Healthcare Workloads

Real-Time AI at the Edge

Real-Time AI at the Edge

NVIDIA’s edge solutions are designed to gather and compute continuous streams of data at the network’s edge. With advanced image, video, and signal processing, AI-embedded medical instruments can aid surgeons in performing less invasive, more targeted surgeries, radiologists in determining diagnoses, and sonographers in performing fast and accurate echocardiograms. Bring healthcare to the edge with the NVIDIA EGX platform.

AI-Ready Hospital Data Center

AI-Ready Hospital Data Center

The AI Enterprise-Ready Platform from NVIDIA and VMware offers a full-stack architecture for today’s converging solutions. Built for resilience and scale, it provides a single platform for both core hospital applications and AI tools, helping deliver a better experience to clinicians and the patients they serve.

 Read Solution Brief: NVIDIA AI Enterprise for Healthcare

On-Demand Cloud Computing

On-Demand Cloud Computing

The latest NVIDIA GPUs are available through all major cloud platforms worldwide. With simplified IT management, compute that can be increased or reduced as needed,  and access to NGC™, a hub of GPU-optimized software for deep learning, machine learning, and HPC, organizations can focus on building solutions, gathering insights, and delivering business value.

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