Treffer: 面向 Web 的中医慢病数据挖掘应用系统的开发.

Objective To develop a Web-oriented traditional Chinese medicine (TCM) chronic disease data mining application system to facilitate the application of medical big data in health status prediction, disease risk evaluation and etc of the chronic disease patients. Methods A TCM chronic disease data mining application system was developed which designed the front-end application interface with HTML5, JavaScript, Ajax, ECharts and etc, constructed the back-end algorithm integration platform with Scikit-learn, TensorFlow and other technologies to integrate data mining algorithms such as reduced dimensional analysis, cluster analysis, correlation analysis, developed the database with MySQL, Navicat and other tools, and applied Python language and Django framework to achieve data interaction. Results The system developed gained advantages in stability, convenience, accuracy, visualized chart and controllability, and gifted the medical staffs who didn't have the knowledge on data mining with the ability to execute medical big data management and analysis independently. Conclusion The system developed enhances the utilization of TCM chronic disease big data and improves informatized management of TCM chronic disease, and is thus worthy promoting practically. [ABSTRACT FROM AUTHOR]

目的:开发一种面向Web的中医慢病数据挖掘应用系统,使医疗大数据更合理地应用于中医慢病患者的健康状态预测、疾病风险评估等场景。方法:采用HTML5、JavaScript、Ajax、ECharts等技术设计前端应用界面,运用Scikit-learn、TensorFlow等技术集成降维分析、聚类分析、相关性分析等数据挖掘算法构建后端算法集成平台,通过MySQL、Navicat等工具设计数据库,应用Python语言、Django框架等实现数据交互,从而实现面向Web的中医慢病数据挖掘应用系统。结果:该系统运行稳定,操作便捷,计算准确、高效,可视化图表美观、可控性强,可以使不具备数据挖掘领域技能的医护人员独立进行医疗大数据的管理与分析。结论:面向Web的中医慢病数据挖掘应用系统提升了中医慢病大数据的利用率,推动了中医慢病管理的信息化建设,具有一定的实际应用价值。 [ABSTRACT FROM AUTHOR]

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