近年来医疗机构的增加导致医学信息数量急剧增加,许多医疗机构无法实时对医疗数据进行监控,为此设计了医学信息实时监控与分析系统。系统的应用服务层中融入了多种算法模型和数据分析模型,帮助系统快速对大量的医学数据进行处理和分析,使系统实时掌握数据的动态变化情况。数据采集模块中融合了子带分解和同步触发技术,子带信号通过并行和串行方式进行同步触发,加快了模块的数据传输速率,并保证同步采样。系统中的医学信息实体识别模型采用交叉共享的结构,能够同时提取数据集的交互特征,提高了模型的识别精度。实验结果显示,该研究系统的数据分析效率最高,整体时间不超过7 000 ms,实体识别精度最大为1。
Abstract
In recent years,the increase of the medical institution has caused a dramatic increase of medical information,many medical institutions can't real-time to monitor medical data,so a real-time monitoring and analysis of medical information system is designed.Several types of application service layer algorithm model and data analysis model are used in the system,which helps the system quickly to deal with a lot of medical data and analysis.The system can grasp the dynamic changes of data in real time.In the data acquisition module,subband decomposition and synchronous trigger technology are integrated.The subband signals are synchronously triggered in parallel and serial ways,which speeds up the data transmission rate of the module and ensures synchronous sampling.The entity recognition model of medical information in the system adopts the structure of cross-sharing,which can simultaneously extract the interactive features of the data set and improve the recognition accuracy of the model.The experiment results show that the data analysis efficiency of this system is the highest,the overall time is less than 7 000 ms,and the entity recognition accuracy is 1.
关键词
医学信息 /
监控分析 /
数据分析模型 /
同步触发 /
实体识别 /
交叉共享
Key words
medical information /
monitoring analysis /
data analysis model /
synchronous trigger /
entity recognition /
cross sharing
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