目的 探讨急性左心衰竭临床护理决策思维人工智能训练系统在新入职护士中的初步应用效果。方法 以急性左心衰竭的发生机制为依据，设计不同病因的急性左心衰竭案例，撰写基于标准化病人的案例对话脚本，利用人工智能自然语言处理技术，形成急性左心衰竭护理虚拟模拟情景；开发包含个人信息、案例训练、考核评价、系统管理4个模块的急性左心衰竭临床护理决策思维人工智能训练系统。2025年5月，将该系统的案例1应用于该院在职的新入职护士中。结果 173名新入职护士共产生411份训练数据。173名新入职护士在急性左心衰竭临床护理决策思维上的得分为（70.99±8.63）分；对于411份训练数据，总体决策正确率的均值为73.53%，训练总响应时间中位数为794.96[四分位数间距（IQR）=777.11] s，决策点响应时间中位数为29.44（IQR=28.78）s。结论 急性左心衰竭临床护理决策思维人工智能训练系统具有可用性，有助于激发新入职护士的学习热情，发现新入职护士在急性左心衰竭临床护理决策思维上的薄弱之处。

Objective To explore the preliminary application effect of the artificial intelligence training system for clinical nursing decision-making thinking in acute left heart failure for the training of newly recruited nurses. Methods Based on the pathogenesis of acute left heart failure，cases of acute left heart failure with different etiologies were designed，and case dialogue scripts based on standardized patients were drafted. By using artificial intelligence natural language processing technology，virtual simulation scenarios for acute left heart failure nursing were created. An artificial intelligence training system for nursing decision-making thinking was finally developed，which includes four modules：personal information，case training，assessment and evaluation，and system management. In May 2025，the system was applied to 173 newly recruited nurses in the hospital. Results A total of 411 training data were generated from 173 newly recruited nurses. The score of newly recruited nurses in clinical nursing decision-making thinking for acute left heart failure was（70.99±8.63） points，with an overall decision-making accuracy rate of 73.53%. The total response time for each training session was 794.96 s[interquartile range（IQR）=777.11]，and the response time for decision point was 29.44 s（IQR=28.78）. Conclusion The artificial intelligence training system for clinical nursing decision-making thinking in acute left heart failure is usable. It is helpful in stimulating the learning enthusiasm of newly recruited nurses，and identifying their weaknesses in clinical nursing decision-making thinking for acute left heart failure.