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20242026
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cs.CL2026

RubricsTree: Scalable and Evolving Open-Ended Evaluation of Personal Health Agents across Health Memory and Medical Skills

Weizhi Zhang, Zechen Li, Hamid Palangi +16

The LLM-empowered personal health agents with user health (sensor) metrics have offered a promising pathway to alleviate global disparities in healthcare access. However, large-sca…

cs.CL2025

A Case Study Exploring the Current Landscape of Synthetic Medical Record Generation with Commercial LLMs

Yihan Lin, Zhirong Bella Yu, Simon Lee

Synthetic Electronic Health Records (EHRs) offer a valuable opportunity to create privacy preserving and harmonized structured data, supporting numerous applications in healthcare.…

cs.CL2025

Clinical ModernBERT: An efficient and long context encoder for biomedical text

Simon A. Lee, Anthony Wu, Jeffrey N. Chiang

We introduce Clinical ModernBERT, a transformer based encoder pretrained on large scale biomedical literature, clinical notes, and medical ontologies, incorporating PubMed abstract…

cs.CL2024

Text Serialization and Their Relationship with the Conventional Paradigms of Tabular Machine Learning

Kyoka Ono, Simon A. Lee

Recent research has explored how Language Models (LMs) can be used for feature representation and prediction in tabular machine learning tasks. This involves employing text seriali…

cs.CL2024

Can Large Language Models abstract Medical Coded Language?

Simon A. Lee, Timothy Lindsey

Large Language Models (LLMs) have become a pivotal research area, potentially making beneficial contributions in fields like healthcare where they can streamline automated billing…

cs.CL2024

Emergency Department Decision Support using Clinical Pseudo-notes

Simon A. Lee, Sujay Jain, Alex Chen +4

In this work, we introduce the Multiple Embedding Model for EHR (MEME), an approach that serializes multimodal EHR tabular data into text using pseudo-notes, mimicking clinical tex…