Suppr超能文献

ClusterRadar:一种用于随时间对空间聚类进行多方法探索的交互式网络工具。

ClusterRadar: An interactive web-tool for the multi-method exploration of spatial clusters over time.

作者信息

Mason Lee, Hicks Blánaid, Almeida Jonas S

机构信息

Division of Cancer Epidemiology and Genetics, National Institutes of Health, Rockville, Maryland, United States of America.

Center for Public Health, Queen's University Belfast, Belfast, United Kingdom.

出版信息

PLoS One. 2025 May 27;20(5):e0322393. doi: 10.1371/journal.pone.0322393. eCollection 2025.

Abstract

Spatial cluster analysis is crucial for understanding localized patterns in geospatial data, with wide-ranging applications for scientific discovery and decision-making. However, the dynamic nature of spatial clusters and the diverse range of clustering methods available can make analysis and interpretation challenging. We introduce ClusterRadar, a web-based tool designed to streamline this process by uniquely prioritizing longitudinal analysis and multi-method comparison of spatial clusters. It empowers users to easily perform clustering with multiple methods, directly compare results, and visualize spatiotemporal patterns through a novel design of linked interactive visualizations. ClusterRadar aims to maximize utility to a broad user base by supporting various geospatial formats and executing entirely within the browser to ensure data privacy. ClusterRadar is available at https://episphere.github.io/ClusterRadar.

摘要

空间聚类分析对于理解地理空间数据中的局部模式至关重要,在科学发现和决策制定方面有广泛应用。然而,空间聚类的动态性质以及可用聚类方法的多样性会使分析和解释具有挑战性。我们引入了ClusterRadar,这是一个基于网络的工具,旨在通过独特地优先考虑空间聚类的纵向分析和多方法比较来简化这一过程。它使用户能够轻松地用多种方法进行聚类,直接比较结果,并通过一种新颖的链接交互式可视化设计来可视化时空模式。ClusterRadar旨在通过支持各种地理空间格式并完全在浏览器内执行以确保数据隐私,从而为广大用户群体最大化效用。可在https://episphere.github.io/ClusterRadar上获取ClusterRadar。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a333/12112157/7d23315db091/pone.0322393.g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验