activity
20232025
most citedTwo Directions for Clinical Data Generation with Large Language Models: Data-to-Label and Label-to-Data

29 citations · 44 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

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…

cs.CL2025

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…

cs.CL2024★ 1 cited

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…

cs.CL2023★ 29 cited

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…

cs.CL2023★ 11 cited

NoteChat: A Dataset of Synthetic Doctor-Patient Conversations Conditioned on Clinical Notes

Junda Wang, Zonghai Yao, Zhichao Yang +5

We introduce NoteChat, a novel cooperative multi-agent framework leveraging Large Language Models (LLMs) to generate patient-physician dialogues. NoteChat embodies the principle th…

cs.LG2023★ 1 cited

Early Prediction of Alzheimers Disease Leveraging Symptom Occurrences from Longitudinal Electronic Health Records of US Military Veterans

Rumeng Li, Xun Wang, Dan Berlowitz +7

Early prediction of Alzheimer's disease (AD) is crucial for timely intervention and treatment. This study aims to use machine learning approaches to analyze longitudinal electronic…

cs.CL2023★ 2 cited

ODD: A Benchmark Dataset for the Natural Language Processing based Opioid Related Aberrant Behavior Detection

Sunjae Kwon, Xun Wang, Weisong Liu +7

Opioid related aberrant behaviors (ORABs) present novel risk factors for opioid overdose. This paper introduces a novel biomedical natural language processing benchmark dataset nam…