3 citations · 5 across the 6 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.LG2026
X-FEMR: A Token-level Explainable Approach for Electronic Health Records Foundation Models using Transformer-based Models
Jie Huang, Pengfei Yin, Zihan Xu +3
Foundation Models for Electronic Health Records (FEMRs) are pretrained on large-scale structured patient data, enabling them to convert longitudinal patient trajectories into gener…
cs.LG2026
Generating synthetic electronic health record data using agent-based models to evaluate machine learning robustness under mass casualty incidents
Roben Delos Reyes, Daniel Capurro, Nicholas Geard
ML models in healthcare are typically evaluated using curated real-world EHR data. A key limitation of such evaluations is that they may fail to assess the robustness of ML models…