3 accepted papers
Large language models (LLMs) have shown remarkable abilities in generating natural texts for various tasks across different domains. However, applying LLMs to clinical settings still poses significant challenges, as it requires specialized knowledge, vocabulary, as well as reliability. In this work,…
We introduce NoteChat, a novel cooperative multi-agent framework leveraging Large Language Models (LLMs) to generate patient-physician dialogues. NoteChat embodies the principle that an ensemble of role-specific LLMs, through structured role-play and strategic prompting, can perform their assigned r…
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 imbalanced medical data, is under-explored. We investigate whether LLMs can augment clinical data for detecting Alzheimer…