AI for Health grantees making an impact
Learn how our grantees and partners are addressing global health challenges with AI for Health resources and grants.
American College of Radiology
American College of Radiology (ACR) gives providers a secure, compliant environment in Azure for testing AI models. They will collaborate on research towards the explainability and generalizability of AI models, and how these tools influence physician confidence levels.
COVID-19 High Performance Computing Consortium
The COVID-19 High Performance Computing Consortium, led by the White House OSTP, gives researchers access to world’s most powerful supercomputing resources to help identify new ways to fight the virus.
DNAstack launched COVID Cloud, an open platform for real-time sharing and analysis of harmonized SARS-CoV-2 genomes and metadata. The databank provides a clearer picture of the emergence and patterns of COVID-19 variants.
Folding@home, a distributed computing project at Washington University in St. Louis, is using AI to discover how the SARS-CoV-2 spike binds to human proteins and a variety of novel binding sites throughout the virus that could be targeted with drugs.
Morehouse School of Medicine
As part of the Atlanta University Center Consortium, Morehouse School of Medicine (MSM) is developing a COVID-19 ‘Return to School’ solution that includes dashboards for operational reporting and collaborating to explore more efficient testing.
State Departments of Health
AI for Health collaborated with Nevada and Washington state health departments to create COVID-19 dashboards to better understand the progress we are making towards ending the pandemic.
Take, the Brazilian leader in chatbots and the smart contacts market, developed a bot to bring official and credible information to the public and connect potential patients to medical teams to avoid overloading Brazilian hospitals.
A grassroots employee volunteer effort at Belgian biopharmaceutical company UCB has identified 150 new molecules that could potentially counteract replication of the SARS-CoV-2 virus and aid in drug therapies as part of the COVID-19 Moonshot initiative.
University of California, Riverside
Harnessing GPU-enabled cloud resources, UC Riverside researchers utilized quantum-based methods to more accurately predict the effectiveness of proposed COVID-19 inhibitors and used CRISPR-Cas12a genome editing tools to better detect the virus.
University of Illinois at Urbana-Champaign (UIUC)
Researchers at UIUC are using GPU-enabled compute systems in various ways including designing peptide inhibitors and simulating the SARS-CoV2 spike protein in a crowded viral environment.
University of Notre Dame
Notre Dame librarians have created a new way to do research by enabling access to curated sets of research literature in the cloud that can also be taken offline for analysis when students and researchers are not on campus due to lockdowns.
BC Cancer is developing the next generation of cancer imaging tools to assist radiologists and cancer researchers in improving detection and assessment of tumors in PET/CT images.
Cascadia Data Alliance
New regional data collaborations are focused on immune checkpoint inhibitors, accurately diagnosing distinct ovarian cancer types, and single-cell genomic sequencing on breast cancer biopsies.
Flu Tracking Collaboration
A unique collaboration across Microsoft, Harvard University, University of Houston, and Northeastern University delivered new findings that track the prevalence of influenza-like illness, based on online browsing data.
Scarlett’s Sunshine Act
Following unanimous passage by the U.S. Congress, Scarlett’s Sunshine Act was signed into law. This legislation improves efforts to better understand and prevent SUID and SUDC by facilitating data collection and insights.
Seattle Children’s Research Institute
Machine learning and data analytics are helping scientists at Seattle Children’s Research Institute uncover the root causes of breathing disorders like Sudden Infant Death Syndrome (SIDS).
SRL Diagnostics uses AI for histopathology to identity severity of cancer in pathology images, starting with breast cancer and extending to colorectal and prostate cancers.
St. Jude Children’s Research Hospital
Harnessing the power of Azure, St. Jude Children’s Research Hospital scientists created the largest cloud-based genomic resource for pediatric cancer and a data-sharing model to accelerate life-saving research.
Business Data Evolution
Business Data Evolution (BDE) uses AI to advance research into methods to identify retinopathy of prematurity, a vision-threatening disorder affecting premature infants which can lead to blindness.
Intelligent Retinal Imaging Systems (IRIS)
Diabetic retinopathy is a leading cause of blindness among working-aged adults across the world. Early detection can reduce the risk of blindness by up to 95%. IRIS can use AI to identify vision threatening forms of disease through the evaluation of images.
UNOS is exploring the use of AI to increase the efficiency, effectiveness, and equity of organ donations and transplants.
BRAC’s community-based approach employs a network of health workers to give people living in poverty access to quality, affordable services. Local health workers can bridge the gap between formal healthcare systems and communities.
Institute for Health Metrics and Evaluation (IHME)
IHME, a global health research organization at the University of Washington School of Medicine, forecasts the COVID-19 pandemic, helping governors, hospital administrators, and vaccine makers mobilize resources.
The Novartis Foundation developed an AI-enabled accelerator of leprosy detection, based on skin lesion images. Now, they are advancing new approaches to improve cardiovascular health and support care for people in low-income settings.
Using AI and data science, PATH works with underserved communities to improve the diagnosis of diseases like tuberculosis and cervical cancer, detect and respond to disease outbreaks, and support efficient and effective health systems.
In partnership with the OpenDP Initiative, Microsoft and Harvard launched SmartNoise, a general purpose open-source differential privacy platform, making it possible to extract useful insights from datasets while still safeguarding privacy.
The Open Data Campaign
The Open Data Campaign enables organizations of all sizes to realize the benefits of data and new technologies, so everyone can access resources to make better decisions and tackle some of the world’s most pressing societal challenges.
University of British Columbia created Federated Learning, a framework with a Centralized Adversary that enables researchers to collaborate with each other and improve models in a privacy-preserving, distributed data-sharing way.