NVIDIA : Doctors Are Superheroes Today, Superhumans Tomorrow

AI is the most important technology of our time, while early detection is the most important medical challenge of our time. Incredible breakthroughs in AI are making it possible for doctors to see disease earlier and better understand it.

That's why NVIDIA founder and CEO Jensen Huang will be speaking at the World Medical Innovation Forum (WMIF) tomorrow in Boston. More than 1,000 worldwide leaders in industry and academia will share recent innovations at the intersection of AI and healthcare - this is the focus of Huang's fireside chat.

NVIDIA's Medical Record

NVIDIA's work in virtual reality gaming, AI and self-driving cars constantly grabs headlines. Hidden in our chart is the great work we do with partners in healthcare.

The earliest applications of CUDA, our GPU computing platform, were in medical imaging and life science. Invented 15 years earlier, iterative reconstruction was a new algorithm in computed tomography that promised X-ray dose reduction but was too computationally expensive. NVIDIA GPUs made it possible for GE Healthcare's family of Revolution CT to reduce radiation by 82 percent.

Ultrasound has also been revolutionized by GPU computing; GE Healthcare's Vivid E95 can perform real-time 4D imaging to see blood flow through the heart.

NVIDIA GPU computing enabled life science researchers at Klaus Schulten's computational biophysics lab at the University of Illinois at Urbana-Champaign to simulate molecular dynamics at a scale 1,000x larger than otherwise possible. This allowed them to create never seen before views of an HIV capsid and the first ever simulation of an entire life form, that of the satellite tobacco mosaic virus.

ThermoFisher Scientific engineers accelerated their gene sequencing algorithm by 250x with NVIDIA GPUs, and created the Ion S5 Next Generation Sequencing system - a breakthrough in both cost and time savings to analyze a targeted gene sequence.

At the University of Stockholm, NVIDIA GPUs enable researcher Erik Lindahl's RELION imaging application to process and reconstruct 3D images of molecular structures. RELION is the imaging software of the Nobel Prize-winning cryogenic electron microscope. Cryo-EM lets researchers freeze molecules in mid-motion and see biological processes at the atomic level for the first time. The journal Nature dubbed Cryo-EM its scientific 'Method of the Year.'

AI Give Doctors Superhuman Powers

Deep learning burst onto the computing scene six years ago when Alex Krizhevsky won ImageNet, the international computer image recognition contest. Krizhevsky used NVIDIA GPUs to train his eight-layer deep neural network, called AlexNet.

Recognizing the importance of this approach of software development, NVIDIA went all-in on deep learning, believing it would lead to advances in AI and help solve problems never before possible. It was a good decision. Today, deep learning software has achieved superhuman pattern recognition capabilities - in vision, sound, speech and many other forms of perception.

This year, we announced the new Volta GPU - the first processor that is equally adept at computer graphics, scientific computing and deep learning. With Volta's Tensor Core architecture, AlexNet can be trained 500x faster than just six years ago. NVIDIA is advancing AI computing at lightning speeds.

Medical imaging researchers have discovered the power of deep learning. Half of the papers presented at last year's MICCAI, the leading medical imaging conference, applied deep learning. We're working with over 300 healthcare startups tackling challenges now possible with deep learning. Together they've raised over $1.5 billion. Arterys, Butterfly Networks, RADLogics, Viz.Ai and Zebra are doing exciting work in medical imaging, with many AI recognition models that are now FDA approved.

The progress is amazing, and this is just the first stage.

The Future

AI is truly great with promise to augment future superhuman doctors. The pace of progress is incredible.

How do we get this technology into the hands of doctors? And how do we integrate this technology into current infrastructure, which was created with great care to protect patient data?

We recently announced a new GPU computing platform, called Clara, that accelerates imaging of different modalities, neural network architectures of all types and any approach of visualization - from rasterization, to volumetric, to ray tracing. Clara is built for the datacenter, extending our offering from embedded in medical devices, workstations, on-prem datacenters, or any and every cloud. Clara can be used to run the latest breakthroughs in medical imaging, virtually, and upgrade the world's 3 million medical instruments instantly.

It's one architecture - with the same software that can run everywhere.

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We partner with leaders in healthcare. In medical imaging, we have great partnerships with GE, Siemens and Philips. We recently announced a new partnership with Canon Medical Systems to put AI supercomputers in hospitals. We have great partnerships with research hospitals like Massachusetts General Hospital, Mayo Clinic, Stanford, and Memorial Sloan Kettering, the National Institutes of Health and exciting startups like Paige.AI and PathAI, which are working on AI-powered computational pathology.

All of us have one purpose - to empower future doctors with superhuman capabilities so that better healthcare can be provided.