SILVER Lab
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-level heterogeneity for treatment effects,
Identify high risk subcohort leading poor health outcomes,
Detect timely and effective treatment strategies,
Predict health outcomes promoting early intervention,
Predict biological age and age acceleration.
Our application focuses on (but not limited to) the following populations
Older adults living with cognition conditions (AD/ADRD)
Patients with multimorbidity
T2D patients with heart or cardiovascular diseases.
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 comparison
Target trial emulation
Time-to-event analysis with time-varying covariates
Prediction of multivariate outcomes using machine learning
Trial design