Visual Analytics based Search-Analyze-Forecast Framework for Epidemiological Time-series Data
Visual Analytics based Search-Analyze-Forecast Framework for Epidemiological Time-series Data
复制标题
基于可视化分析的流行病学时间序列数据搜索分析预测框架
DOI：
10.1109/vis4pandemres60343.2023.00006
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Gonen T
中科院分区：
文献类型：
--
作者：
Gonen T
在2019冠状病毒病大流行期间，公共卫生专业人员密集使用疾病统计数据的时间序列，如病例或疫苗接种数量，以估计其地区与其他地区的比较情况，并估计国内的未来情况。传统的可视化往往在高级比较功能和系统支持预测方面受到限制。本文提出了一种可视化的分析方法，以支持数据驱动的预测的基础上的搜索分析预测过程，包括多度量，多标准的时间序列搜索方法和数据驱动的预测技术。这些都是由一个可视化框架的支持，多个时间序列的综合比较。我们通过从全球公共卫生专家那里获得迭代反馈来设计我们的方法，并对其进行定量和定性评估。
The COVID-19 pandemic has been a period where time-series of disease statistics, such as the number of cases or vaccinations, have been intensively used by public health professionals to estimate how their region compares to others and estimate what future could look like at home. Conventional visualizations are often limited in terms of advanced comparative features and in supporting forecasting systematically. This paper presents a visual analytics approach to support data-driven prediction based on a search-analyze-predict process comprising a multi-metric, multi-criteria time-series search method and a data-driven prediction technique. These are supported by a visualization framework for the comprehensive comparison of multiple time-series. We inform the design of our approach by getting iterative feedback from public health experts globally, and evaluate it both quantitatively and qualitatively.
影响因子：
4.6
作者：
Padilla L;Hosseinpour H;Fygenson R;Howell J;Chunara R;Bertini E
通讯作者：
Bertini E
DOI：
10.1109/tvcg.2021.3114828
发表时间：
2021-07
影响因子：
5.2
作者：
Saiful Khan;P. H. Nguyen;Alfie Abdul-Rahman;B. Bach;Min Chen;Euan Freeman;C. Turkay
通讯作者：
Saiful Khan;P. H. Nguyen;Alfie Abdul-Rahman;B. Bach;Min Chen;Euan Freeman;C. Turkay
绘制 COVID-19 危机可视化图景
DOI：
10.1145/3411764.3445381
发表时间：
2021
期刊：
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
影响因子：
--
作者：
Zhang, Yixuan;Sun, Yifan;Padilla, Lace;Barua, Sumit;Bertini, Enrico;Parker, Andrea G
通讯作者：
Parker, Andrea G