4 papers
MLB: A Scenario-Driven Benchmark for Evaluating Large Language Models in Clinical Applications
Qing He, Dongsheng Bi, Jianrong Lu +20
The proliferation of Large Language Models (LLMs) presents transformative potential for healthcare, yet practical deployment is hindered by the absence of frameworks that assess re…
Toward expert-level motivational interviewing for health behavior improvement with LLMs
Run-ze Hu, Yang Yang, Yi-hang Yang +8
Background: Motivational interviewing (MI) is an effective counseling approach for promoting health behavior change, but its impact is constrained by the need for highly trained hu…
CliniChat: A Multi-Source Knowledge-Driven Framework for Clinical Interview Dialogue Reconstruction and Evaluation
Jing Chen, Zhihua Wei, Wei Zhang +2
Large language models (LLMs) hold great promise for assisting clinical interviews due to their fluent interactive capabilities and extensive medical knowledge. However, the lack of…
Intelligent Understanding of Large Language Models in Traditional Chinese Medicine Based on Prompt Engineering Framework
Yirui Chen, Qinyu Xiao, Jia Yi +2
This paper explores the application of prompt engineering to enhance the performance of large language models (LLMs) in the domain of Traditional Chinese Medicine (TCM). We propose…