首页|基于BERT模型的医疗安全事件智能分类研究与实践

基于BERT模型的医疗安全事件智能分类研究与实践

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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.
Study and Practice on Intelligent Classification of Medical Safety Incidents Based on BERT Model
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.Re-sult/Conclusion The model is used to classify 466 medical safety incidents reported by clinical departments from January to November 2022,and F1 value reaches 0.66.The application of BERT model in the classification and evaluation of medical safety incidents can im-prove work efficiency and timeliness,and help timely intervene in medical safety risks.

medical safety incidentsBERTdeep learningintelligent classification

赵从朴、袁达、朱溥珏、周炯、陈政、彭华

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中国医学科学院北京协和医院 北京 100730

医疗安全事件 BERT 深度学习 智能分类

北京协和医学院中央高校基本科研业务费项目

3332022087

2024

医学信息学杂志
中国医学科学院

医学信息学杂志

CSTPCD
影响因子:1.348
ISSN:1673-6036
年,卷(期):2024.45(1)
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