Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction
This research will develop and validate machine learning enhanced predictive models improving the allocation of critical care pharmacists to intensive care units to reduce adverse drug events.
Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction
This research will use artificial intelligence and machine learning to create prediction tools integrated into visualization dashboards to guide critical care pharmacists in preventing adverse drug events.
ACHIEVE: Successfully Achieving and Maintaining Euglycemia During Pregnancy for Type 2 Diabetes Through Technology and Coaching
To assist pregnant individuals with pre-pregnancy type 2 diabetes with Medicaid coverage in reaching and maintaining normal blood sugars, this research will develop, test, and evaluate a digital health solution called ACHIEVE that includes a mobile health application, a provider dashboard, continuous glucose monitoring, and team-based coaching for medical needs and nonmedical health-related social needs.
COMputerized PAtient-centered Collaborative Technology (COMPACT) to Support Personalized Decision Making in Breast Cancer
This research will develop and evaluate a COMputerized PAtient-centered Collaborative Technology (COMPACT) to support personalized breast cancer decision making.