EHRAdapt: Adapting Pretrained Language Models to Electronic Health Records with Semantic Priors for Rare Clinical Events

arXiv:2609.34007 · cs.AI · Submitted 2026-09-27 · Read on arXiv

cs.AI

Submitted: 2026-09-27

Updated: 2026-09-27

Terminology

• Embeddings — 38× in this paper · explained in 2 episodes
• Ablation — 19× in this paper · explained in 1 episode
• Transformer — 15× in this paper · explained in 2 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Downstream Tasks — 6× in this paper · explained in 2 episodes
• Foundation Model — 5× in this paper · explained in 3 episodes
• Foundation Models — 4× in this paper · explained in 7 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• In International Conference on Learning Representations — 3× in this paper
• Representation Learning — 3× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Kaiser Permanente Northern California — 2× in this paper
• Model-Agnostic — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Ontology — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Unified Medical Language System — 1× in this paper

Sources

• The Llama 3 Herd of Models
• PORTER: Language-Grounded Event Representations for Portable Structured EHR Foundation Models
• Large Language Models are Powerful Electronic Health Record Encoders
• MOTOR: A Time-To-Event Foundation Model For Structured Medical Records
• 2 OLMo 2 Furious
• EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
• Prompting Large Language Models for Zero-Shot Clinical Prediction with Structured Longitudinal Electronic Health Record Data

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