World Medical Innovation Forum — NVIDIA and
the American College of Radiology today announced a collaboration
to enable thousands of radiologists nationwide to create and use AI
for diagnostic radiology in their own facilities, using their own
data, to meet their own clinical needs.
Following a successful three-month pilot program by both
parties, ACR is integrating the NVIDIA Clara™ AI toolkit into the
newly announced ACR Data Science Institute® ACR AI-LAB™, a free
software platform that will be made available to more than 38,000
ACR members and other radiology professionals to build, share,
locally adapt and validate AI algorithms, while also ensuring
patient data stays protected at the local institution.
The NVIDIA Clara AI toolkit is a key part of the NVIDIA Clara
developer platform, which is designed to enable software-defined
medical instruments and intelligent workflows. A platform to create
data and algorithm pipelines, NVIDIA Clara consists of libraries
for data and image processing, AI model processing, and
visualization. For AI, the toolkit includes libraries for data
annotation, model training, model adaptation, model federation and
large-scale deployment.
Making the vision of the ACR AI-LAB a reality requires the
collaboration of the entire ecosystem, including industry leaders
GE Healthcare, Nuance and NVIDIA, along with a vast network of
healthcare startups and leading research institutes. NVIDIA Clara
powers GE Healthcare’s Edison AI platform and the Nuance AI
Marketplace, both of which are supporting the AI-LAB and are key
solutions for the deployment of AI within the radiology
workflow.
“This collaboration marks a significant milestone in an
extraordinary ACR Data Science Institute project, helping enable
the launch of the ACR AI-LAB, giving radiologists in any practice
environment an opportunity to become involved in AI development at
their own institutions, using their own patient data to meet their
own clinical needs,” said Bibb Allen Jr., M.D., FACR and chief
medical officer of the Data Science Institute at the American
College of Radiology.
“NVIDIA builds platforms that democratize the use of AI and we
purpose-built the Clara AI toolkit to give every radiologist the
opportunity to develop AI tools that are customized to their
patients and their clinical practice,” said Kimberly Powell, vice
president of Healthcare at NVIDIA. “Our successful pilot with the
ACR is the first of many that will make AI more accessible to the
entire field of radiology.”
Successful Pilot Paves Way to Democratized AI for
HealthcareAn initial pilot with the Ohio State University
(OSU) and the Massachusetts General Hospital and Brigham and
Women’s Hospital’s Center for Clinical Data Science (CCDS) helped
NVIDIA and ACR define the assets and pathways necessary to enable
facilities to work together and with industry to refine AI
algorithms without sharing potentially sensitive patient data.
Bringing an AI model to the patient data, instead of patient data
to the model, can help increase diversity in algorithm training,
facilitate validation of the algorithms and enable radiologists to
learn the steps needed to adapt algorithms to their institutions’
clinical needs.
Using the NVIDIA Clara AI toolkit, OSU was able to quickly
import a pre-trained model developed by CCDS. This model was
customized to local variables and successfully labeled OSU data for
further testing and improvement of the algorithm, all of which took
place behind their own firewall. It resulted in a highly accurate
and enhanced cardiac computed tomography angiography model, and the
shared approach reduced algorithm training, validation and testing
times by days.
“This software will offer radiologists, without computer
programming experience, the ability to build and improve AI
algorithms without the need to share their data,” said Keith
Dreyer, D.O., Ph.D., chief data science officer at Partners
Healthcare and associate professor of radiology at Harvard Medical
School. “Algorithms typically work best within the sites where they
were trained, but those limited training sets are not always
representative of the population at large. Training AI models on
data from diverse sites helps ensure resiliency while reducing
algorithm bias, resulting in improved inference across broader
populations.”
“Enabling a network of artificial intelligence between hospitals
will create more robust algorithms, greater efficiencies and likely
lead to better patient outcomes,” said Dr. Richard White, chair of
the department of Radiology and Medical Imaging Informatics at the
Ohio State University Wexner Medical Center. “This will give us
access to high-quality algorithms that will help us accelerate deep
learning and machine learning in healthcare.”
The architecture used in the pilot program, powered by the
NVIDIA Clara AI toolkit, enables data aggregation, image
annotation, image pre-processing and transformation, algorithm
transfer and local computing for algorithm improvement, all of
which are necessary to achieve the ultimate goal of the
democratization of AI.
Ecosystem Support for ACR AI-LAB and NVIDIA
ClaraStrong support for the ACR AI-LAB comes from NVIDIA
Clara AI platform users and industry leaders GE Healthcare and
Nuance.
“Democratizing AI takes not only state-of-the-art technology,
but also close collaboration among industry leaders,” said Keith
Bigelow, senior vice president of Edison Portfolio Strategy at GE
Healthcare. “By supporting the ACR community’s AI-LAB efforts and
harnessing the power of NVIDIA’s Clara AI platform, GE Healthcare
can lower costs and improve patient outcomes by accelerating the
number of algorithms created and seamlessly deployed to
Edison-powered healthcare devices and applications in hospitals
nationwide. GE Healthcare looks forward to enabling the fastest
path to compliant and productive use of ACR AI-LAB algorithms in
our world leading medical devices and workflow applications.”
“Combining the strength of the NVIDIA Clara AI platform with the
scale of the Nuance AI Marketplace for Diagnostic Imaging will
empower ACR AI-LAB developers to rapidly build and seamlessly
deploy AI algorithms into the existing clinical workflows of over
70 percent of all radiologists across more than 5,800 connected
healthcare facilities,” said Karen Holzberger, vice president and
general manager of Healthcare Diagnostics at Nuance. “Furthermore,
the ubiquitous footprint of Nuance PowerScribe radiology reporting
and PowerShare image-sharing solutions provides subscribers of our
AI Marketplace with immediate access to the largest storefront of
imaging AI algorithms that can be automatically integrated into the
radiology reporting and interpretation tools they use every
day.”
ACR-AI LAB Planned Debut and AvailabilityThe
initial version of ACR AI-LAB will be shown at the 2019 ACR Annual
Meeting in Washington, from May 18-22. Attendees will be able to
explore and experiment with the AI tools necessary to modify and
refine AI models.
Soon after, ACR plans to provide online access and sample data
from publicly available patient datasets.
The ACR AI-LAB builds upon the ACR TRIAD (Transfer of Images and
Data), a platform that already connects thousands of radiology
practices for ACR research, accreditation and registry program.
Through the ACR AI-LAB, these same radiologists will now be
provided with user-friendly computational tools that will help them
learn about annotating datasets and training AI models as well as
sample the AI tools that can be used to train and modify existing
AI algorithms.
About the American College of RadiologyThe
American College of Radiology (ACR), founded in 1924, is a
professional medical society dedicated to serving patients and
society by empowering radiology professionals to advance the
practice, science, and professions of radiological care.
About NVIDIA NVIDIA’s (NASDAQ: NVDA) invention
of the GPU in 1999 sparked the growth of the PC gaming market,
redefined modern computer graphics and revolutionized parallel
computing. More recently, GPU deep learning ignited modern AI — the
next era of computing — with the GPU acting as the brain of
computers, robots and self-driving cars that can perceive and
understand the world. More information at
http://nvidianews.nvidia.com/.
For further information, contact:Kasia
JohnstonPR Manager for Healthcare and IndustriesNVIDIA
Corporation+1-415-813-8859kasiaj@nvidia.com
Shawn FarleyMedia RelationsAmerican College of
Radiology+1-703-648-8936pr@acr.org
Meghan SwopeMedia RelationsAmerican College of
Radiology+1-703-390-9822pr@acr.org
Certain statements in this press release including, but not
limited to, statements as to: NVIDIA and the American College of
Radiology accelerating adoption of AI in diagnostic radiology
across thousands of hospitals; NVIDIA Clara AI toolkit enabling ACR
AI-LAB and giving ACR members and radiology professionals the
ability to develop and deploy AI; the benefits and impact of the
collaboration between NVIDIA and the ACR, including the use of AI;
ACR integrating the NVIDIA Clara AI toolkit into ACR AI-LAB, its
availability and its ability to protect patient data; the benefits,
performance and abilities of NVIDIA Clara and ACR AI-LAB; making
ACR AI-LAB a reality requiring the collaboration of the entire
ecosystem; the collaboration enabling the launch of ACR AI-LAB and
giving radiologists an opportunity to become involved in AI
development; NVIDIA’s platform democratizing the use of AI; the
NVIDIA Clara platform giving radiologists the opportunity to
develop customized AI tools; the collaboration with ACR being one
of many that will make AI more accessible to the entire field of
radiology; the benefits and impact of being able to refine AI
algorithms and use the software without sharing patient data; the
benefits of bringing the AI model to patient data; the software
enabling radiologists to build and improve AI algorithms without
the need to share data; the benefits of training AI models on data
from diverse sites, including improved inference across broader
populations; enabling a network of artificial intelligence between
hospitals creating more robust algorithms, greater efficiencies and
likely leading to better patient outcomes, and it giving access to
high-quality algorithms that will accelerate deep learning and
machine learning in healthcare; and what the architecture enables
and its contribution to the democratization of AI; the benefits of
the AI-LAB and NVIDIA’s Clara platform for GE Healthcare and it
enabling the fastest path to the use of these products in its
devices and applications; NVIDIA Clara and Nuance AI Marketplace
empowering the deployment of AI algorithms and Nuance products
providing access to imaging AI algorithms and their integration
into use; and the availability of ACR AI-LAB are forward-looking
statements that are subject to risks and uncertainties that could
cause results to be materially different than expectations.
Important factors that could cause actual results to differ
materially include: global economic conditions; our reliance on
third parties to manufacture, assemble, package and test our
products; the impact of technological development and competition;
development of new products and technologies or enhancements to our
existing product and technologies; market acceptance of our
products or our partners’ products; design, manufacturing or
software defects; changes in consumer preferences or demands;
changes in industry standards and interfaces; unexpected loss of
performance of our products or technologies when integrated into
systems; as well as other factors detailed from time to time in the
most recent reports NVIDIA files with the Securities and Exchange
Commission, or SEC, including, but not limited to, its annual
report on Form 10-K and quarterly reports on Form 10-Q. Copies of
reports filed with the SEC are posted on the company’s website and
are available from NVIDIA without charge. These forward-looking
statements are not guarantees of future performance and speak only
as of the date hereof, and, except as required by law, NVIDIA
disclaims any obligation to update these forward-looking statements
to reflect future events or circumstances.
© 2019 NVIDIA Corporation. All rights reserved. NVIDIA, the
NVIDIA logo and NVIDIA Clara are trademarks and/or registered
trademarks of NVIDIA Corporation in the U.S. and other countries.
Other company and product names may be trademarks of the respective
companies with which they are associated. Features, pricing,
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notice.
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