Nature July 15, 2024
Peixing Wan, Zigeng Huang, Wenjun Tang, Yulan Nie, Dajun Pei, Shaofen Deng, Jing Chen, Yizhi Zhou, Hongru Duan, Qingyu Chen & Erping Long

Abstract

Reception is an essential process for patients seeking medical care and a critical component influencing the healthcare experience. However, current communication systems rely mainly on human efforts, which are both labor and knowledge intensive. A promising alternative is to leverage the capabilities of large language models (LLMs) to assist the communication in medical center reception sites. Here we curated a unique dataset comprising 35,418 cases of real-world conversation audio corpus between outpatients and receptionist nurses from 10 reception sites across two medical centers, to develop a site-specific prompt engineering chatbot (SSPEC). The SSPEC efficiently resolved patient queries, with a higher proportion of queries addressed in...

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Topics: AI (Artificial Intelligence), Nursing, Provider, Technology
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