29 citations · 30 across the 4 of their papers we have counts for
4 papers
DualAlign: Generating Clinically Grounded Synthetic Data
Rumeng Li, Xun Wang, Hong Yu
Synthetic clinical data are increasingly important for advancing AI in healthcare, given strict privacy constraints on real-world EHRs, limited availability of annotated rare-condi…
A New NMT Model for Translating Clinical Texts from English to Spanish
Rumeng Li, Xun Wang, Hong Yu
Translating electronic health record (EHR) narratives from English to Spanish is a clinically important yet challenging task due to the lack of a parallel-aligned corpus and the ab…
Exploring LLM Multi-Agents for ICD Coding
Rumeng Li, Xun Wang, Hong Yu
To address the limitations of Large Language Models (LLMs) in the International Classification of Diseases (ICD) coding task, where they often produce inaccurate and incomplete pre…
Two Directions for Clinical Data Generation with Large Language Models: Data-to-Label and Label-to-Data
Rumeng Li, Xun Wang, Hong Yu
Large language models (LLMs) can generate natural language texts for various domains and tasks, but their potential for clinical text mining, a domain with scarce, sensitive, and i…