Innovative predictive model to anticipate steroid-induced hyperglycemia and guide insulin regimens
Identify optimal, individualized treatment policies for insulin dosing in the context of systemic glucocorticoids.
AI/ML Implementation & Enabling Infrastructure
DIHI has developed a diverse portfolio of Augmented Intelligence & machine learning models and is responsible for the underlying infrastructure to facilitate their development and implementation into Duke Health. DIHI applies devops principles to the entirety of its infrastructure design to achieve reproducible, monitored, automated, and tested deployments of innovations at-scale for Duke.
Utilization of machine learning to read transthoracic echocardiograms: Project normal echocardiogram
To develop and validate a computer algorithm to correctly estimate left ventricular ejection fraction (LVEF) as an initial step toward a fully automated echocardiogram evaluation.
A population health approach to advance care planning in primary care
A population-health based pathway to provide ACP at the Duke Outpatient Clinic.
ED LOS: Predictive analytics to reduce emergency department length of stay for youth with behavioral health disorders
Reducing Emergency Department length of stay through population-based predictive modeling.
Rational coronary care unit triage for stable patients with NSTEMI
Predicting the development of in-hospital complications requiring ICU care in initially stable patients with NSTEMI.
PROMISE: Perioperative Risk Optimization with Machine Learning for an Improved Surgical Experience
Optimization of perioperative care through machine learning.
CALYPSO: Machine Learning for Assessing & Managing Surgical Outcomes
Building statistical models and using machine learning principles to predict the absolute and relative risks of surgical complications for specific patients.
Duke Connected Care Chronic Kidney Disease Care Improvement Project
Use of validated statistical models on Duke data to predict the rate of decompensation for patients with Chronic Kidney Disease (CKD) while also creating a novel model of team-based care, Population Rounding TM.