NIH SCHARE Grand Challenges: Science Collaborative for Health and Artificial intelligence Reduction of Errors
Introduction
NIMHD has launched three complementary challenges spanning the chronic disease disparities research cycle—from making complex data usable, to modeling individuals and populations, to generating better real-world data for monitoring, prevention, and action.
- Reimagine data integration and computations: Transform fragmented data into reusable, AI-ready research resources and advance innovative computational methods and interoperable data ecosystems.
- Build and validate digital twins and synthetic populations: Create scientifically valid, representative, and reusable models that integrate real-world data and support discovery, prevention, intervention development, and public health decision-making.
- Create smart devices and sensing technologies: Advance innovative, interoperable, and scalable technologies that generate AI-ready data to improve early detection, continuous monitoring, prevention, and management of chronic diseases.
Competition phases, timelines, and prizes vary by challenge. See more information here.
Please contact Dr. Karen Cielo, Director of Research Development, if you are interested in applying or would like to discuss the opportunity.