This NOSI is intended to encourage interest in the small business community to develop various approaches, technologies, and tools to address the health issues of maternal morbidity and mortality by achieving a wide array of outcomes, such as 1) the identification, phenotyping, subtyping, and stratification of patients at a greater risk of MMM, 2) multi-level interventions to address racial disparities in MMM, and 3) clinical decision-making that considers social and cultural biases.
Furthermore, this NOSI focuses on the development and validation of tools, technologies, and approaches, including artificial intelligence (AI) and machine learning, that indicate states of increased risk for and presence of MMM. This includes but is not limited to development of tools and technologies that:
- Measure factors associated with increased risk for MMM, including but not limited to blood pressure, heart rate, maternal/fetal physiology, or pupil dilation and facial expression.
- Measure biometrics associated with the onset and exacerbation of various diseases of MMM, including but not limited to depression or preeclampsia.
- Predict risk from a variety of data sources, for example, medical charts and electronic health records.
- Alert patients and clinicians to potential risk factors.
- Suggest various prevention and treatment approaches.
For more information, visit: https://grants.nih.gov/grants/guide/notice-files/NOT-EB-21-001.html