Statistical Information Integration and Learning for multiVariate hEalthcaRe data
SILVER Lab
[Our lab is seeking highly motivated master/PhD students and postdoctoral fellows to join our research group! Please do not hesitate to contact the PI if you are interested in any of these researches.]
SILVER lab focuses on developing novel analytical methods in health data science. The developed methods aim to better
Depict patient/hospital-level heterogeneity for treatment effects;
Identify high risk subcohort leading poor health outcomes;
Detect time-varying treatment/exposure effects;
Predict health outcomes promoting early intervention;
Predict and evaluate biological age.
Our application focuses on (but not limited to) the following populations
Older adults living with high frailty, e.g., AD/ADRD;
Patients with multimorbidity;
Patients with heart/cardiovascular diseases/T2D.
The developed methods / methods under development include (but not limited to)
Integrating multivariate secondary/surrogate outcomes;
Casual inference and machine learning;
Integrating summary information from external data;
Target trail emulation.
Our lab also offers collaboration services and consulting, including (but not limited to)
(Time varying) propensity score matching/weighting for treatment/exposure comparison
Target trial emulation
Real-world evidence/data integration
Time-to-event analysis with time-varying covariates
Prediction of multivariate outcomes using machine learning
Epidemiological design