基于BERT模型的医疗安全事件智能分类研究与实践

Study and Practice on Intelligent Classification of Medical Safety Incidents Based on BERT Model

目的/意义改进医疗安全事件分类评估模式,提升工作效率和时效性。方法/过程选取既往医疗安全事件数据进行预处理,利用BERT模型进行训练、测试、迭代优化,构建医疗安全事件智能分类预测模型。结果/结论利用该模型对2022年1-11月临床科室上报的466例医疗安全事件进行分类,F1值达0.66。将BERT模型应用于医疗安全事件分类评估辅助,可提升工作效率和时效性,有助于及时干预医疗安全风险隐患。

Purpose/Significance To improve the classification and evaluation mode of medical safety incidents,and to improve work efficiency and timeliness.Method/Process The data of previous medical safety incidents are pre-processed,BERT model is used for training,testing and iterative optimization,and an intelligent classification and prediction model for medical safety incidents is built.Result/Conclusion The model is used to classify 466 medical safety incidents reported by clinical departments from January to November 2022,and F 1 value reaches 0.66.The application of BERT model in the classification and evaluation of medical safety incidents can improve work efficiency and timeliness,and help timely intervene in medical safety risks.