基于ECharts的医疗数据交互式可视化研究  

Research on Interactive Visualisation of Medical Data Based on ECharts

作　　者：陈思楠 陈吉平 黄红倩 潘伟权 CHEN Sinan;CHEN Jiping;HUANG Hongqian;PAN Weiquan(School of Mathematics and Statistics,Yulin Normal University,Yulin 537000,China)

机构地区：[1]玉林师范学院数学与统计学院,广西玉林537000

出　　处：《现代信息科技》2024年第14期76-80,共5页Modern Information Technology

基　　金：大学生创新创业训练计划项目(202110606020)。

摘　　要：文章对基于ECharts的医疗数据交互式可视化进行了深入研究。首先,报告了使用ECharts在高效医疗数据可视化分析领域的应用现状。研究对两个案例进行了详细调查:第一个案例探讨在不同学习率(0.001和0.000 01)下,ECharts如何有效生成准确率和损失率曲线,以及这些曲线如何清晰展示深度学习模型在训练过程中的动态变化;第二个案例则针对睡眠健康和生活方式数据集,展示不同职业群体中失眠、无障碍和睡眠呼吸暂停的分布比例。通过这两个案例,不仅加深了对ECharts在医疗数据可视化中的应用理解,还为未来医疗数据分析和深度学习领域的研究提供了新视角和有力的实践指导,突显了ECharts在数据科学与可视化领域的关键作用。This paper presents an in-depth study of interactive visualisation of medical data based on ECharts.Firstly,the current application status of using ECharts in the field of efficient medical data visualisation and analysis is reported.The study investigates two cases in detail.The first case explores how ECharts can efficiently generate accuracy and loss rate curves at different learning rates(0.001 and 0.00001)and how these curves can clearly demonstrate the dynamic change of a Deep Learning model during the training process.The second case targets the sleep health and lifestyle dataset to show the distribution ratio of insomnia,accessibility and sleep apnoea in different occupational groups.Through the two cases,this paper not only deepens the application understanding of ECharts in medical data visualisation,but also provides new perspectives and strong practical guidance for future research on the fields of medical data analysis and Deep Learning,highlighting the key role of ECharts in the fields of data science and visualisation.

关 键 词：ECharts 可视化 交互式 医疗数据 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]