PORTER is a language-grounded EHR foundation model that uses text descriptions for events and a numeric pathway, matching fixed-vocabulary performance on 74 tasks while recovering 97.1% AUROC on unseen vocabularies and outperforming on MIMIC.
Fries, Conor K
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Fused code-value tokenization improves mortality AUROC from 0.891 to 0.915 and other clinical outcome predictions, while certain temporal encodings like event order match or exceed time tokens with shorter sequences.
citing papers explorer
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PORTER: Language-Grounded Event Representations for Portable Structured EHR Foundation Models
PORTER is a language-grounded EHR foundation model that uses text descriptions for events and a numeric pathway, matching fixed-vocabulary performance on 74 tasks while recovering 97.1% AUROC on unseen vocabularies and outperforming on MIMIC.
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Representation Before Training: A Fixed-Budget Benchmark for Generative Medical Event Models
Fused code-value tokenization improves mortality AUROC from 0.891 to 0.915 and other clinical outcome predictions, while certain temporal encodings like event order match or exceed time tokens with shorter sequences.