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20242026
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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.LG2026

GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring

Zechen Li, Keerthana Natarajan, Weizhi Zhang +11

Continuous glucose monitoring (CGM) provides a dense view of daily metabolic physiology, yet existing generic time-series and CGM-specific foundation models often encode glucose tr…

cs.LG2026

Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning

Hao Zhou, Simon A. Lee, Cyrus Tanade +12

Biosignals acquired from different locations on the body often provide temporally ordered views of the same underlying physiological process. However, most existing self supervised…

cs.LG2026

Wavelet-Driven Masked Multiscale Reconstruction for PPG Foundation Models

Megha Thukral, Cyrus Tanade, Simon A. Lee +10

Wearable foundation models have the potential to transform digital health by learning transferable representations from large-scale biosignals collected in everyday settings. While…

cs.LG2025

Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025

Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90

The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…

cs.LG2025

HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series

Simon A. Lee, Cyrus Tanade, Hao Zhou +13

Wearable sensors provide abundant physiological time series, yet the principles governing their predictive utility remain unclear. We hypothesize that temporal resolution is a fund…