Construction of a Multilingual Hospital Intelligent Customer Service System for Xinjiang Based on Large Language Models

Corresponding author: Pengcheng Yang, yang_pc@yeah.net

DOI: 10.12201/bmr.202609.00005

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  Abstract: Objective/Significance: To address the issues of complex medical procedures and low triage efficiency caused by language barriers in multi-ethnic regions of Xinjiang, this study develops an efficient and equitable localized intelligent customer service system, aiming to improve healthcare accessibility and the medical experience for ethnic minority patients.Methods/Process: Based on the Qwen3 large language model and retrieval-augmented generation (RAG) technology, a trilingual interactive system (Chinese, Uyghur, and Kazakh) was constructed, integrating multilingual voice interaction and RAG-based knowledge retrieval. The system adopts lightweight deployment strategies to adapt to the limited network conditions in border areas and was piloted for three months at a tertiary hospital in Xinjiang.Results/Conclusion: The appointment registration success rate increased from 60% to 92%, the average response time decreased from 8 minutes to 15 seconds, and user satisfaction among multilingual patients reached 91%. The system effectively alleviates language barriers, significantly enhances hospital service efficiency and patient satisfaction, and provides a replicable technical paradigm for leveraging artificial intelligence to promote healthcare equity in ethnic regions.

  Key words: Slarge language model; multilingual; hospital intelligent customer service

  Submit time: 3 September 2026

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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• ID	Submit time	Number	Download
  1	2026-04-22	10.12201/bmr.202609.00005V1	Download

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