Data Analytics and AI
We harness data analytics and machine learning to improve the quality of clinical care, diagnose gaps in health services, and guide strategic decision-making in healthcare.
Examples of our work include building predictive models for specific health outcomes, analyzing operational data at the point of care, and developing social listening insights from large social media and textual data sets. We work closely with implementation agencies and health departments to develop capacity for data monitoring, analysis, and rapid response.
Relevant Projects
NATIVE RISE-Risk Identification for Suicide and Enhanced care for Native Americans
Longtime tribal-academic research partners will optimize and evaluate NATIVE-RISE, a systems level strategy to suicide prevention that combines service-ready tools based on predictive analytics with risk-stratified evidence-based care for Native American adults.
GAVI: Digital Health Information Monitoring, Evaluation, and Learning Plan Implementation
The major goal of this project is to monitor and evaluate scaled digital health interventions to improve key immunization outcomes in select low- and middle-income countries. Some of the interventions being studied are DHIS2, OpenLMIS, and e-surveillance amongst others.
Gender Bias in Open AI Algorithms
Testing open AI algorithms for gender bias in the information provided and decision-making based on gender stereotypes.