inspect ./work/privacy-conscious-synthetic-patient-data
Generating High-Fidelity Privacy-Conscious Synthetic Patient Data for Causal Effect Estimation with Multiple Treatments
Privacy-conscious synthetic patient data
- Date
- Role
- Coauthor and co-inventor
- Type
- publication
- Source
- Frontiers in Artificial Intelligence publication and US patent record, reviewed 2026-10-27
This work describes a process for generating realistic synthetic patient data with known causal effects for multiple treatments while treating patient privacy as a primary design constraint.
The research was published in Frontiers in Artificial Intelligence. The related US patent covers high-fidelity privacy-conscious synthetic patient data for causal-effect estimation with multiple treatments.