AI for Health

Professor Amanda Randles at Duke University is using the power of Azure to conduct hundreds of millions of simulations required to help more patients have access to critical ventilators.

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.

Folding@home, a distributed computing project at Washington University in St. Louis, is using AI to better understand the relationship between proteins and diseases with a goal of accelerating new therapeutics, including for COVID-19.

Our community-based healthcare approach employs a wide network of community health workers to ensure that people living in poverty can access high quality, affordable services. Health workers are social entrepreneurs who ensure a continuum of care, bridging the gap between formal healthcare systems and communities.

The COVID-19 High Performance Computing Consortium, led by the White House, gives researchers access to world’s most powerful supercomputing resources that can help identify new ways to fight the virus.

The CDDI, led by the Fred Hutchinson Cancer Research Center, aims to establish a regional data sharing ecosystem. By enabling collaboration, data sharing, and research, the CDDI will help each participating organization advance its research capabilities and lead to health and science breakthroughs to help patients.

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.

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%. Intelligent Retinal Imaging Systems (IRIS) can use AI to identify vision threatening forms of disease through the evaluation of images.

Every year, there are over 200,000 new cases of leprosy but increasing early diagnosis can help limit transmission of the disease. We partnered with the Novartis Foundation to develop an AI-enabled digital health tool, which can accelerate early detection, helping the world toward leprosy elimination.

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.

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).

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.

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.

Researchers at UIUC are using GPU-enabled compute systems in various ways including designing peptide inhibitors and simulating the SARS-CoV-2 spike protein in a crowded viral environment.

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.