The American Heart Association (AHA) Institute for Precision Cardiovascular Medicine awarded $2 million in the form of three grants for seven investigators centering on advanced artificial intelligence, machine learning and precision medicine. The Institute for Precision Cardiovascular Medicine has introduced the Amazon Web Services (AWS)-based Precision Medicine Platform a hub in the cloud for AI and machine learning to support precision medicine-centric studies.
The grants are listed below.
· American Heart Association Grand Challenge: Precision Health and Precision Medicine grant
· American Heart Association and Amazon Web Services 4.0 Data Grant Portfolio: Artificial Intelligence and Machine Learning grant
· American Heart Association and Amazon Web Services 4.0 Data Grant Portfolio: Artificial Intelligence and Machine Learning Training Grants
The American Heart Association established the Institute for Precision Cardiovascular Medicine, which has funded over 93 grants totaling more than $30.2 million since 2014. Grant applicants focus on projects geared toward artificial intelligence, machine learning, precision medicine and precision health.
AHA Deal with Amazon
Amazon is currently in a fierce battle for the cloud infrastructure services market against Microsoft Azure and others. Based on the Gartner Magic Quadrant for Cloud Infrastructure, Amazon leads the market with Microsoft fighting to catch up. Creative, integrated, value-added partnerships tied to specific verticals, sectors and industry reflect the vendors’ need to capture greater market share and ultimately demonstrate the transformative value of AI and machine learning for example, ultimately in the form of return of investment that could be measured in myriad of ways in the medical research context. The AHA and Amazon Web Services (AWS) inked a partnership committed to precision medicine in the Summer of 2016.
This most recent grant round includes an “Amazon Web Services” (AWS) credit for $50,000 per year for use on the American Heart Association Precision Medicine Platform.® Powered by AWS, this central hub for the cardiovascular and stroke research community offers access to a vast and diverse array of datasets and cloud-based workspaces enabling “state-of-the-art, high-performance computing, analytics and collaborations to accelerate scientific discovery.”
What is Eligible for Grant Consideration?
AHA’s Institute for Precision Cardiovascular Medicine will consider research involving digital images, electronic health records, genetics, wearable devices, smartphone apps, community engagement data as well as social determinants of health are considered eligible.
Progress with Duke University
These new grants reflect growing momentum of the AHA Precision Medicine Platform. By 2018, AHA inked an arrangement with the Duke Clinical Research Institute to design and develop machine learning programs on the platform in the drive to support research collaboration and better patient care. Jennifer Hall, PhD, Chief of the AHA Institute for Precision Cardiovascular Medicine, recently told Jessica Kent with HealthITAnalytics.com that “The strategic alliance that we’ve made with Duke is so important, because we have the experts who have the deep knowledge of all of the artificial intelligence and machine learning tools that are available. The partnership allows the American Heart Association and Duke to come together to create new tools that are not even available today.”
Grand Challenge Grant: One awardee who will receive $1 million over 4 years
Cui Tao, Ph.D., The University of Texas Health Science Center at Houston –
Project: Artificial intelligence-aided personalization on dual antiplatelet therapy duration for patients who underwent coronary stent implantation
Artificial Intelligence and Machine Learning Grant: Four awardees, each receiving $200,000 over 2 years
Andrew McCulloch, Ph.D., University of California, San Diego
Project: Cardiac atlases for machine learning in congenital heart disease
Arash Kheradvar, Ph.D., University of California, Irvine
Project: Cloud-based artificial intelligence platform for automatic segmentation and analysis of pediatric cardiac MRI datasets
Ona Wu, Ph.D., Massachusetts General Hospital
Project: Automated detection of severe brain edema development in cardiac arrest survivors
Xue Feng, Ph.D., University of Virginia, Charlottesville
Project: A cloud-based framework for multi-institutional clinical studies incorporating artificial intelligence
Artificial Intelligence and Machine Learning Training Grant: Two awardees, each receiving $100,000 over 2 years
Avinash Parnandi, Ph.D., New York University School of Medicine
Project: Measurement tools for clinical and home rehabilitation after stroke
Erlei Zhang, Ph.D., University of Texas Southwestern Medical Center
Project: Developing an artificial Intelligence-based radiotherapy cardiotoxicity analysis platform