Machine Learning for Learning Health Systems
Welcome to the ML4LHS Lab home page.
The Machine Learning for Learning Health Systems (ML4LHS) Lab focuses on translational issues related to the implementation of machine learning (ML) models within health systems. Effective translation of ML in clinical care requires attention to model development, evaluation, and implementation, and it needs to consider clinical workflows, resource constraints, and the practice of medicine more broadly. Our lab is geared towards studying these issues in applied settings, sharing software tools to foster reproducibility, and in using our findings to guide clinicians, health systems, and policy.
Students
Jie Cao, MPH
PhD candidate, Computational Medicine and Bioinformatics
Elliott Brannon, MPH
MD/PhD (PhD candidate), Health Infrastructures and Learning Systems
Lab Alumni
Shreyas Ramani, MHI
Senior Healthcare Data Analyst, Caravan Health
Graduated from MHI program
Pritika Dasgupta, MPH, MHI
Biomedical Informatics PhD Student, University of Pittsburgh School of Medicine
Graduated from MHI program
Sajjad Seyedsalehi, MSc, MSc
Industrial Engineering PhD Student, University of Michigan
Etiowo Usoro, MHI
Business Intelligence Analyst, Kaiser Permanente
Graduated from MHI program
Tianshi Wang, MHI
Data Scientist, Trexquant Investment LP
Graduated from MHI program
Jin Xiu Lu, MHI
Graduated from MHI program
Adharsh Murali
Health Insights Machine Learning Engineer, Providence Health and Services
Graduated from MHI program
Sean Meyer, MBA
Senior Scientist at the Michigan Institute for Data Science (MIDAS)
Graduated from Design Science PhD program