Fengchen Liu

Abstract Large language models (LLMs) show promise in supporting differential diagnosis, but their performance is challenging to evaluate due to the unstructured nature of their responses, and their accuracy compared to existing diagnostic tools is not well characterized.

Author Affiliations Zike Jiang,1,2,3,6 Jiantao Chen,1,2,3 Jiewei Du,1,2,3 Tiesheng Liu,1,2,3 Xiaofeng Li,1,2,3 Huibin Yu,1,2,3 Qi Zhang,1,2,3 Yimeng Hu,1,2,3 Fengchen Liu,1,2,3 Xinsheng Yu,4,5,* and Zhonghai Zhou1,2,3,7 1Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, Shandong, China 2Shandong Provincial Key Laboratory of Marine Monitoring Instrument Equipment Technology, Qingdao, Shandong, China 3National Engineering and...

The following information is missing from the Funding section: TCP and EM gratefully acknowledge support from the Meaningful Modeling of Epidemiological Data (MMED) program, a NIH-funded joint initiative under the University of Florida, the South African Centre for Epidemiological Modelling and Analysis (SACEMA), and the African Institute for Mathematical Sciences (AIMS) (NIH NIGMS R25GM102149 to J.R.C. Pulliam and A. Welte).