• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

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

BodyMapR:一个R包和Shiny应用程序,旨在生成癌症病变的解剖可视化图。

BodyMapR: an R package and Shiny application designed to generate anatomical visualizations of cancer lesions.

作者信息

Miller David M, Shalhout Sophia Z

机构信息

Division of Hematology/Oncology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.

Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA.

出版信息

JAMIA Open. 2022 Mar 4;5(1):ooac013. doi: 10.1093/jamiaopen/ooac013. eCollection 2022 Apr.

DOI:10.1093/jamiaopen/ooac013
PMID:35274087
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8903180/
Abstract

OBJECTIVES

Structured real-world data (RWD), such as those found in cancer registries, provide a rich source of information regarding the natural history of cancer. Interactive data visualizations of cancer lesions can provide insights into certain clinical tumor characteristics (CTC). Software that can be integrated into an oncological data collection effort and generate anatomical data visualizations of CTC are limited.

MATERIALS AND METHODS

We created BodyMapR: an R package and Shiny application that generates anatomical visualizations of cancer lesions from structured data.

RESULTS

BodyMapR is a Shiny application that transposes structured data from REDCap onto an anatomical map to yield an interactive data visualization.

CONCLUSIONS

BodyMapR is freely available under the MIT license and can be obtained from GitHub. BodyMapR is executed in R and deployed as a Shiny application. It can be integrated into an existing cancer research platform and produces an interactive data visualization of CTC.

摘要

目的

结构化的真实世界数据(RWD),如癌症登记处的数据,提供了关于癌症自然史的丰富信息来源。癌症病变的交互式数据可视化可以提供对某些临床肿瘤特征(CTC)的见解。能够集成到肿瘤学数据收集工作中并生成CTC解剖数据可视化的软件有限。

材料与方法

我们创建了BodyMapR:一个R包和Shiny应用程序,可从结构化数据生成癌症病变的解剖可视化。

结果

BodyMapR是一个Shiny应用程序,可将来自REDCap的结构化数据转换到解剖图上,以产生交互式数据可视化。

结论

BodyMapR根据麻省理工学院许可免费提供,可从GitHub获取。BodyMapR在R中执行并作为Shiny应用程序部署。它可以集成到现有的癌症研究平台中,并生成CTC的交互式数据可视化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a50/8903180/f46fd5ee7591/ooac013f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a50/8903180/cfb2abbb9817/ooac013f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a50/8903180/f9343879ddcd/ooac013f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a50/8903180/f46fd5ee7591/ooac013f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a50/8903180/cfb2abbb9817/ooac013f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a50/8903180/f9343879ddcd/ooac013f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a50/8903180/f46fd5ee7591/ooac013f3.jpg

相似文献

1
BodyMapR: an R package and Shiny application designed to generate anatomical visualizations of cancer lesions.BodyMapR:一个R包和Shiny应用程序,旨在生成癌症病变的解剖可视化图。
JAMIA Open. 2022 Mar 4;5(1):ooac013. doi: 10.1093/jamiaopen/ooac013. eCollection 2022 Apr.
2
StoryboardR: an R package and Shiny application designed to visualize real-world data from clinical patient registries.StoryboardR:一个R包和Shiny应用程序,旨在可视化来自临床患者登记处的真实世界数据。
JAMIA Open. 2023 Jan 6;6(1):ooac109. doi: 10.1093/jamiaopen/ooac109. eCollection 2023 Apr.
3
GENETEX-a GENomics Report TEXt mining R package and Shiny application designed to capture real-world clinico-genomic data.GENETEX——一个基因组报告文本挖掘R包和Shiny应用程序,旨在获取真实世界的临床基因组数据。
JAMIA Open. 2021 Sep 28;4(3):ooab082. doi: 10.1093/jamiaopen/ooab082. eCollection 2021 Jul.
4
Unipept Visualizations: an interactive visualization library for biological data.Unipept可视化:一个用于生物数据的交互式可视化库。
Bioinformatics. 2022 Jan 3;38(2):562-563. doi: 10.1093/bioinformatics/btab590.
5
Advancing Nursing Research Through Interactive Data Visualization With R Shiny.通过 R Shiny 的交互式数据可视化推进护理研究。
Biol Res Nurs. 2023 Jan;25(1):107-116. doi: 10.1177/10998004221121109. Epub 2022 Aug 26.
6
Thinking Outside the Box: Developing Dynamic Data Visualizations for Psychology with Shiny.跳出框框思考:使用Shiny为心理学开发动态数据可视化
Front Psychol. 2015 Dec 1;6:1782. doi: 10.3389/fpsyg.2015.01782. eCollection 2015.
7
SynRio: R and Shiny based application platform for cyanobacterial genome analysis.SynRio:基于R和Shiny的蓝藻基因组分析应用平台。
Bioinformation. 2015 Sep 30;11(9):422-5. doi: 10.6026/97320630011422. eCollection 2015.
8
netGO: R-Shiny package for network-integrated pathway enrichment analysis.netGO:用于网络集成通路富集分析的 R-Shiny 软件包。
Bioinformatics. 2020 May 1;36(10):3283-3285. doi: 10.1093/bioinformatics/btaa077.
9
CHOIRBM: An R package for exploratory data analysis and interactive visualization of pain patient body map data.CHOIRBM:一个用于疼痛患者身体图谱数据探索性数据分析和交互式可视化的 R 包。
PLoS Comput Biol. 2022 Oct 27;18(10):e1010496. doi: 10.1371/journal.pcbi.1010496. eCollection 2022 Oct.
10
GRcalculator: an online tool for calculating and mining dose-response data.GRcalculator:一款用于计算和挖掘剂量反应数据的在线工具。
BMC Cancer. 2017 Oct 24;17(1):698. doi: 10.1186/s12885-017-3689-3.

引用本文的文献

1
The Merkel Cell Carcinoma Patient Registry: From Promise to Prototype to Patient.默克尔细胞癌患者登记处:从承诺到原型再到患者。
J Registry Manag. 2022 Spring;49(1):4-9.
2
Exploring Cancer Incidence, Risk Factors, and Mortality in the Lleida Region: Interactive, Open-source R Shiny Application for Cancer Data Analysis.探索莱里达地区的癌症发病率、风险因素和死亡率:用于癌症数据分析的交互式开源R Shiny应用程序。
JMIR Cancer. 2023 Apr 20;9:e44695. doi: 10.2196/44695.
3
StoryboardR: an R package and Shiny application designed to visualize real-world data from clinical patient registries.

本文引用的文献

1
The Merkel Cell Carcinoma Patient Registry: From Promise to Prototype to Patient.默克尔细胞癌患者登记处:从承诺到原型再到患者。
J Registry Manag. 2022 Spring;49(1):4-9.
2
Immunotherapy for Nonmelanoma Skin Cancer: Facts and Hopes.免疫疗法治疗非黑素瘤皮肤癌:现状与展望。
Clin Cancer Res. 2022 Jun 1;28(11):2211-2220. doi: 10.1158/1078-0432.CCR-21-2971.
3
GENETEX-a GENomics Report TEXt mining R package and Shiny application designed to capture real-world clinico-genomic data.GENETEX——一个基因组报告文本挖掘R包和Shiny应用程序,旨在获取真实世界的临床基因组数据。
StoryboardR:一个R包和Shiny应用程序,旨在可视化来自临床患者登记处的真实世界数据。
JAMIA Open. 2023 Jan 6;6(1):ooac109. doi: 10.1093/jamiaopen/ooac109. eCollection 2023 Apr.
JAMIA Open. 2021 Sep 28;4(3):ooab082. doi: 10.1093/jamiaopen/ooab082. eCollection 2021 Jul.
4
Immunotherapy for Non-melanoma Skin Cancer.非黑色素瘤皮肤癌的免疫疗法。
Curr Oncol Rep. 2021 Aug 27;23(11):125. doi: 10.1007/s11912-021-01120-z.
5
gganatogram: An R package for modular visualisation of anatograms and tissues based on ggplot2.gganatogram:一个基于ggplot2的用于解剖图和组织模块化可视化的R包。
F1000Res. 2018 Sep 28;7:1576. doi: 10.12688/f1000research.16409.2. eCollection 2018.
6
The biology and treatment of Merkel cell carcinoma: current understanding and research priorities.默克尔细胞癌的生物学和治疗:当前的认识和研究重点。
Nat Rev Clin Oncol. 2018 Dec;15(12):763-776. doi: 10.1038/s41571-018-0103-2.
7
Merkel cell polyomavirus status is not associated with clinical course of Merkel cell carcinoma.默克尔细胞多瘤病毒状态与默克尔细胞癌的临床病程无关。
J Invest Dermatol. 2011 Aug;131(8):1631-8. doi: 10.1038/jid.2011.115. Epub 2011 May 12.
8
Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.研究电子数据采集(REDCap)——一种用于提供转化研究信息学支持的元数据驱动方法和工作流程。
J Biomed Inform. 2009 Apr;42(2):377-81. doi: 10.1016/j.jbi.2008.08.010. Epub 2008 Sep 30.