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作 者:赵从朴[1] 袁达[1] 朱溥珏 周炯[1] 陈政[1] 彭华[1] ZHAO Congpu;YUAN Da;ZHU Pujue;ZHOU Jiong;CHEN Zheng;PENG Hua(Peking Union Medical College Hospital,Chinese Academy of Medical Sciences,Beijing 100730,China)
机构地区:[1]中国医学科学院北京协和医院,北京100730
出 处:《医学信息学杂志》2024年第1期27-32,38,共7页Journal of Medical Informatics
基 金:北京协和医学院中央高校基本科研业务费项目(项目编号:3332022087)。
摘 要: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.
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