Background: The fatality of adverse drug reactions (ADR) has become one of the major causes of the non-natural disease deaths globally, with the issue of drug safety emerging as a common topic of concern. Objective: T...Background: The fatality of adverse drug reactions (ADR) has become one of the major causes of the non-natural disease deaths globally, with the issue of drug safety emerging as a common topic of concern. Objective: The personalized ADR early warning method, based on contextual ontology and rule learning, proposed in this study aims to provide a reference method for personalized health and medical information services. Methods: First, the patient data is formalized, and the user contextual ontology is constructed, reflecting the characteristics of the patient population. The concept of ontology rule learning is then proposed, which is to mine the rules contained in the data set through machine learning to improve the efficiency and scientificity of ontology rule generation. Based on the contextual ontology of ADR, the high-level context information is identified and predicted by means of reasoning, so the occurrence of the specific adverse reaction in patients from different populations is extracted. Results: Finally, using diabetes drugs as an example, contextual information is identified and predicted through reasoning, to mine the occurrence of specific adverse reactions in different patient populations, and realize personalized medication decision-making and early warning of ADR.展开更多
目的构建以"预防为主"的大学生心理问题智能预警系统。方法采用自尊量表、心理控制源量表、社会支持量表、青少年生活事件量表和大学生人格问卷(U P I)对安徽省12所不同层次的高校共890名大学生进行测查,使用SPSS 16.0和AM OS...目的构建以"预防为主"的大学生心理问题智能预警系统。方法采用自尊量表、心理控制源量表、社会支持量表、青少年生活事件量表和大学生人格问卷(U P I)对安徽省12所不同层次的高校共890名大学生进行测查,使用SPSS 16.0和AM OS 7.0进行统计分析,在V isual S tud io 2008开发平台下,利用C#语言、SQL Server等技术构建B/S形式的预警系统。结果①U P I得分与自尊、心理控制源、社会支持和生活事件之间存在显著相关(-x±s=9.76±6.88,29.12±3.81,11.32±3.48,14.94±8.72,P<0.01);②生活事件对心理健康(U P I)既有直接效应也有间接效应;③试运行结果显示本系统预警效果良好。结论本预警系统实现了从源头上对心理问题的潜在危险因素进行预警,提高心理问题预警的灵敏度,可以在高校心理咨询中心推广使用。展开更多
文摘Background: The fatality of adverse drug reactions (ADR) has become one of the major causes of the non-natural disease deaths globally, with the issue of drug safety emerging as a common topic of concern. Objective: The personalized ADR early warning method, based on contextual ontology and rule learning, proposed in this study aims to provide a reference method for personalized health and medical information services. Methods: First, the patient data is formalized, and the user contextual ontology is constructed, reflecting the characteristics of the patient population. The concept of ontology rule learning is then proposed, which is to mine the rules contained in the data set through machine learning to improve the efficiency and scientificity of ontology rule generation. Based on the contextual ontology of ADR, the high-level context information is identified and predicted by means of reasoning, so the occurrence of the specific adverse reaction in patients from different populations is extracted. Results: Finally, using diabetes drugs as an example, contextual information is identified and predicted through reasoning, to mine the occurrence of specific adverse reactions in different patient populations, and realize personalized medication decision-making and early warning of ADR.
文摘目的构建以"预防为主"的大学生心理问题智能预警系统。方法采用自尊量表、心理控制源量表、社会支持量表、青少年生活事件量表和大学生人格问卷(U P I)对安徽省12所不同层次的高校共890名大学生进行测查,使用SPSS 16.0和AM OS 7.0进行统计分析,在V isual S tud io 2008开发平台下,利用C#语言、SQL Server等技术构建B/S形式的预警系统。结果①U P I得分与自尊、心理控制源、社会支持和生活事件之间存在显著相关(-x±s=9.76±6.88,29.12±3.81,11.32±3.48,14.94±8.72,P<0.01);②生活事件对心理健康(U P I)既有直接效应也有间接效应;③试运行结果显示本系统预警效果良好。结论本预警系统实现了从源头上对心理问题的潜在危险因素进行预警,提高心理问题预警的灵敏度,可以在高校心理咨询中心推广使用。
