Learning Continuous Patient Trajectories from Electronic Health Records
cs.LG
Submitted: 2026-09-28
Updated: 2026-09-28
Sources
- Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations
- Longitudinal Flow Matching for Trajectory Modeling
- Neural Controlled Differential Equations for Irregular Time Series
- Auto-Encoding Variational Bayes
- Deep Kalman Filters
- Structured Inference Networks for Nonlinear State Space Models
- Causal Transformer for Estimating Counterfactual Outcomes
- Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data
- TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
- A multimodal and temporal foundation model for virtual patient representations at healthcare system scale
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