AI for Health
AI for Health empowers researchers and organizations with AI to improve the health of people and communities around the world.
About the program
Health is a global issue that impacts every person and transcends every border. Technology plays an important role in advancing research and improving access to care for underserved populations. We are tackling some of the toughest challenges in health by collaborating with nonprofits and researchers and providing access to AI and expertise.
Quest for discovery
Accelerating medical research to advance the prevention, diagnoses, and treatment of diseases.
Global health insights
Increasing our shared understanding of health and longevity to protect against global health crises.
Health equity
Reducing health inequity and improving access to care for underserved populations.
Research capabilities
Supporting fundamental research capabilities, including data collaboratives and differential privacy.
Addressing Sudden Infant Death Syndrome
Machine learning and data analytics are helping scientists at Seattle Children’s Research Institute uncover the root causes of breathing disorders like SIDS (Sudden Infant Death Syndrome).
Working to eliminate leprosy
Every year, there are over 200,000 new cases of leprosy but increasing early diagnosis can help limit transmission of the disease. Together, Microsoft and the Novartis Foundation are developing an AI-enabled digital health tool, which can accelerate early detection, helping the world toward leprosy elimination.
Preventing blindness from diabetic retinopathy
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.
Accelerating research collaboration across borders
The Cascadia Data Discovery Initiative (CDDI), led by the Fred Hutchinson Cancer Research Center and powered by Microsoft, aims to establish a regional data sharing ecosystem. By enabling collaborations, data sharing, and data-driven research, the CDDI will help each participating organization advance its research capabilities and lead to health and science breakthroughs to help patients.
Connecting rural communities with health services
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.
Harnessing powerful tools for health equity
PATH advances health equity by aligning innovation with the needs of underserved communities around the world. Using AI and data science, PATH works to improve the diagnosis of diseases like tuberculosis and cervical cancer, detect and respond to disease outbreaks, and support efficient and effective health systems.