AUTHOR=Quan Xiaoxiao , Wang Kejun , Pan Junjie , Fang Zhiyu 
  
TITLE=Artificial intelligence in outpatient management: a simulation-based study in a Chinese tertiary hospital
  
JOURNAL=Frontiers in Artificial Intelligence
  
VOLUME=Volume 8 - 2025
  
YEAR=2026
  
URL=https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1696586
  
DOI=10.3389/frai.2025.1696586
  
ISSN=2624-8212
  
ABSTRACT=The Chinese healthcare system faces significant challenges such as an aging population and uneven resource distribution, necessitating technological innovations to enhance service efficiency and quality. This study explores the application, potential value, and challenges of artificial intelligence (AI) in outpatient management in China using simulated data and a physician survey. Simulation results, based on a comparison between an LSTM model and a traditional ARIMA model, demonstrate that the deep learning-based approach outperforms in predicting outpatient flow, improving forecasting accuracy by approximately 15%. Under simulated conditions, AI implementation reduced patient waiting times by about 30% and increased doctors’ work efficiency and satisfaction, as supported by survey responses. These findings suggest that AI can optimize resource allocation and patient experience in outpatient settings. However, this study is primarily based on simulation, and real-world applicability may be limited. Additional concerns regarding data privacy, regulatory compliance, and physician acceptance remain critical.