中国医疗设备2024，Vol.39Issue(3)：53-57,79,6.DOI:10.3969/j.issn.1674-1633.2024.03.009
基于机器学习对呼吸机报警分析
Analysis of Ventilator Alarms Based on Machine Learning
刘强 1郭瑞 2王勤 3孙凯1
作者信息
- 1. 北京医院 器材处,北京 100730
- 2. 北京医院 呼吸与危重症科,北京 100730
- 3. 北京医院 医务处,北京 100730
- 折叠
摘要
Abstract
Objective To study the ventilation alarms of ventilators in clinical use by applying machine learning methods,obtain the important parameters affecting the alarms and the alarm prediction model,identify invalid alarms and give clinical hints,so that the clinic can respond to the ventilator alarms efficiently to avoid the negative effects of alarm fatigue and other negative impacts.Methods A respiratory data management platform was established that conformed to standard data processes.According to the alarm information of single center ventilator,the characteristic values were analyzed and the important parameters were sorted.Hyperparameter optimization modeling was used to predict the true or false alarm.The confusion matrix and receiver operating characteristic(ROC)were used to validate the machine learning model.Results The test set of 5936 ventilation alarms was evaluated,with 88%invalid alarms rate(recall rate was 0.88).The model accuracy was 0.94,and the precision was 0.78,the area under ROC curve was 0.92.The F1 score was 0.82.Conclusion The use of machine learning facilitates clinical single-center data modeling can timely analyze and obtain the important parameters and alarm predictions of the real alarm of the ventilator,and through the ventilator data management platform,it can effectively prompt the clinical invalid alarms,thus reducing the pressure of the alarms on the healthcare personnel and improving the quality of medical care.关键词
呼吸机/数据接口/报警项目/机器学习/重要特征变量Key words
ventilator/data interface/alarm items/machine learning/important feature variables分类
医药卫生引用本文复制引用
刘强,郭瑞,王勤,孙凯..基于机器学习对呼吸机报警分析[J].中国医疗设备,2024,39(3):53-57,79,6.
