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…
Representation Before Training: A Practical Benchmark for Generative Medical Event Model Tokenization
Inhyeok Lee, Luke Solo, Michael C. Burkhart +5
Generative medical event models use tokenized sequences of patient timelines as input, but practical guidance on the many decisions around tokenization is limited. We benchmark qua…
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…
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…