RESEARCH
Our research is at the intersection of
healthcare + computer science + pharmacy + data science
Our goal is to develop data-driven methods that can leverage electronic health record data with artificial intelligence and computational methods to make medication use safer and more effective for critically ill patients.
Medications are causal agents of both positive outcomes and adverse events. We are interested in incorporating medication data to make meaningful insights at the ICU bedside.
1
Prediction Modeling
2
Causal Inference
3
NLP/LLM Methods
Can we develop AI/ML methods to incorporate medication data to predict comprehensive medication management needs and adverse drug events?
Medications are causal agents: can we advance our understanding of how medications impact patient outcomes?
How can large language models be harnessed to improve medication safety and efficacy?
