Article

DualAlign: Generating Clinically Grounded Synthetic Data

2025-09-12

Abstract excerpt

Synthetic clinical data are increasingly important for advancing AI in healthcare, given strict privacy constraints on real-world EHRs, limited availability of annotated rare-condition data, and systemic biases in observational datasets. While large language models (LLMs) can generate fluent clinical text, producing synthetic data that is both realistic and clinically meaningful remains challenging. We introduce D...

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Literature Corpus work: 2ad01df3-67f0-5007-898d-563d86417b8c
DOI: 10.1101/2025.09.09.25335422

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