What You Should Know:
– NVIDIA and Massachusetts General Brigham Hospital
researchers develop an AI model that determines whether a person showing up in
the emergency room with COVID-19 symptoms will need supplemental oxygen hours
or even days after an initial exam.
– The ultimate goal of this model is to predict the
likelihood that a person showing up in the emergency room will need
supplemental oxygen, which can aid physicians in determining the appropriate
level of care for patients, including ICU placement.
Researchers at NVIDIA
and Massachusetts General Brigham
Hospital have developed an artificial
intelligence (AI) model that determines whether a person showing up in the
emergency room with COVID-19
symptoms will need supplemental oxygen hours or even days after an initial
exam.
The original AI model, named CORISK, was developed by scientist Dr. Quanzheng Li at Mass General Brigham. It combines medical imaging and health records to help clinicians more effectively manage hospitalizations at a time when many countries may start seeing the second wave of COVID-19 patients.
EXAM (EMR CXR AI Model) & Results
To develop an AI model that doctors trust and that
generalizes to as many hospitals as possible, NVIDIA and Mass General Brigham
embarked on an initiative called EXAM (EMR CXR AI Model) the largest,
most diverse federated
learning initiative with 20 hospitals from around the world.
In just two weeks, the global collaboration achieved a model
with .94 area under the curve (with an AUC goal of 1.0), resulting in excellent
prediction for the level of oxygen required by incoming patients. The federated
learning model will be released as part of NVIDIA
Clara on NGC in the coming weeks.
Leveraging NVIDIA’s Clara Federated Learning Framework
Using NVIDIA Clara
Federated Learning Framework, researchers at individual hospitals were able
to use a chest X-ray, patient vitals and lab values to train a local model and
share only a subset of model weights back with the global model in a
privacy-preserving technique called federated learning.
The ultimate goal of this model is to predict the likelihood
that a person showing up in the emergency room will need supplemental oxygen,
which can aid physicians in determining the appropriate level of care for
patients, including ICU placement.
Dr. Ittai Dayan, who leads the development and deployment of AI at Mass General Brigham, co-led the EXAM initiative with NVIDIA and facilitated the use of CORISK as the starting point for the federated learning training. The improvements were achieved by training the model on distributed data from a multinational, diverse dataset of patients across North and South America, Canada, Europe, and Asia.
Participating Hospitals in EXAM Initiative
In addition to Mass Gen Brigham and its affiliated
hospitals, other participants included: Children’s National Hospital in Washington,
D.C.; NIHR Cambridge Biomedical Research Centre; The Self-Defense Forces
Central Hospital in Tokyo; National Taiwan University MeDA Lab and MAHC and
Taiwan National Health Insurance Administration; Kyungpook National
University Hospital in South Korea; Faculty of Medicine, Chulalongkorn
University in Thailand; Diagnosticos da America SA in Brazil; University of
California, San Francisco; VA San Diego; University of Toronto; National
Institutes of Health in Bethesda, Maryland; University of Wisconsin-Madison
School of Medicine and Public Health; Memorial Sloan Kettering Cancer Center in
New York; and Mount Sinai Health System in New York.
Each of these hospitals used NVIDIA Clara to
train its local models and participate in EXAM. Rather than needing to pool
patient chest X-rays and other confidential information into a single location,
each institution uses a secure, in-house server for its data. A separate
server, hosted on AWS, holds the global deep neural network, and each
participating hospital gets a copy of the model to train on its own dataset.
NVIDIA Announces Partnership with GSK’s AI-Powered Lab
for Discovery of Medicines and Vaccines
In addition, the new AI model, NVIDIA today announced a
partnership with global healthcare company GSK and its AI group, which is
applying computation to the drug and vaccine discovery process. GSK has
recently established a new London-based AI hub, one of the first of its kind,
which will leverage GSK’s significant genetic and genomic data to improve the
process of designing and developing transformational medicines and vaccines.
Located in London’s rapidly growing Knowledge Quarter, GSK’s hub will utilize biomedical data, AI methods, and advanced computing platforms to unlock genetic and clinical data with increased precision and scale. The GSK AI hub, once fully operational, will be home to its U.K.-based AI team, including GSK AI Fellows, a new professional training program, and now scientists from NVIDIA.
NVIDIA Building UK’s Most Powerful Supercomputer,
Dedicated to AI Research in Healthcare
NVIDIA today announced that it is building the United
Kingdom’s most powerful supercomputer, which it will make available to U.K.
healthcare researchers using AI to solve pressing medical challenges, including
those presented by COVID-19.
Expected to come online by year end, the “Cambridge-1”
supercomputer will be an NVIDIA DGX SuperPOD™ system capable of delivering more
than 400 petaflops of AI performance and 8 petaflops of Linpack performance,
which would rank it No. 29 on the latest TOP500 list of the world’s most powerful
supercomputers. It will also rank among the world’s top 3 most energy-efficient
supercomputers on the current Green500 list.
