4 papers
Federated generative event models for tokenized electronic health records
Michael C. Burkhart, Luke Solo, Inhyeok Lee +8
Electronic health record foundation models are limited by institutionally siloed data and substantial performance degradation under cross-site transfer. We evaluated federated trai…
Efficient Generative Prediction for EHR Foundation Models: The SCOPE and REACH Estimators
Luke Solo, Matthew B. A. McDermott, William F. Parker +3
Generative foundation models trained on tokenized electronic health record (EHR) timelines show promise for clinical outcome prediction via Monte Carlo sampling of simulated future…
Representation Before Training: A Fixed-Budget Benchmark for Generative Medical Event Models
Inhyeok Lee, Luke Solo, Michael C. Burkhart +3
Every prediction from a generative medical event model is bounded by how clinical events are tokenized, yet input representation is rarely isolated from other system and architectu…
Quantifying surprise in clinical care: Detecting highly informative events in electronic health records with foundation models
Michael C. Burkhart, Bashar Ramadan, Luke Solo +2
We present a foundation model-derived method to identify highly informative tokens and events in electronic health records. Our approach considers incoming data in the entire conte…