3 papers
cs.LG2026
One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
Zilin Jing, Vincent Jeanselme, Yuta Kobayashi +6
Clinical events captured in Electronic Health Records (EHR) are irregularly sampled and may consist of a mixture of discrete events and numerical measurements, such as laboratory v…
cs.LG2025
CEHR-XGPT: A Scalable Multi-Task Foundation Model for Electronic Health Records
Chao Pang, Jiheum Park, Xinzhuo Jiang +5
Electronic Health Records (EHRs) provide a rich, longitudinal view of patient health and hold significant potential for advancing clinical decision support, risk prediction, and da…
cs.LG2025
FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records
Chao Pang, Vincent Jeanselme, Young Sang Choi +9
Foundation models (FMs) promise to address core limitations of traditional supervised machine learning: (i) reliance on large amounts of labeled data, (ii) task specificity, and (i…