11 citations · 35 across the 18 of their papers we have counts for
5 papers · 1 filter
README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP
Zonghai Yao, Nandyala Siddharth Kantu, Guanghao Wei +6
The advancement in healthcare has shifted focus toward patient-centric approaches, particularly in self-care and patient education, facilitated by access to Electronic Health Recor…
Do Physicians Know How to Prompt? The Need for Automatic Prompt Optimization Help in Clinical Note Generation
Zonghai Yao, Ahmed Jaafar, Beining Wang +2
This study examines the effect of prompt engineering on the performance of Large Language Models (LLMs) in clinical note generation. We introduce an Automatic Prompt Optimization (…
Large Language Models are In-context Teachers for Knowledge Reasoning
Jiachen Zhao, Zonghai Yao, Zhichao Yang +1
In this work, we study in-context teaching (ICT), where a teacher provides in-context example rationales to teach a student to reason over unseen cases. Human teachers are usually…
BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing
Hieu Tran, Zhichao Yang, Zonghai Yao +1
To enhance the performance of large language models (LLMs) in biomedical natural language processing (BioNLP) by introducing a domain-specific instruction dataset and examining its…
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…