A “SHINY” APPLICATION: INTERACTIVE ONLINE MAPPING FOR THE CASE CAPTURE PERCENTAGES OF EXPECTED CANCER CASES IN THE UNIVERSITY OF KANSAS CANCER CENTER

Published 30 April 2021 •  vol 2  •  no 1  • 


Authors:

 

Dinesh Pal Mudaranthakam, Department of Biostatistics, University of Kansas Medical Center, Kansas, USA
Junhao Liu, Department of Biostatistics, University of Kansas Medical Center, Kansas, USA
Alex Karanevich, Department of Biostatistics, University of Kansas Medical Center, Kansas, USA
John Keighley, Department of Biostatistics, University of Kansas Medical Center, Kansas, USA
Byron Gajewski, Department of Biostatistics, University of Kansas Medical Center, Kansas, USA

Abstract:

 

In the last few decades, data visualization and analysis techniques have grown rapidly. Creating interactive web-based geographical maps is a common technique that transforms raw data into easily-understandable graphics. RStudio’s “Shiny” is an R package and an open source tool that is increasingly being used to build interactive web applications. We used Shiny to develop our web application: an online, interactive geographical map, based on the Surveillance, Epidemiology, and End Results (SEER) database. This app was developed to demonstrate case capture percentages of cancer cases for the University of Kansas Cancer Center which covers all the counties of Kansas and a few counties of Missouri. With this interactive web-based map, it is quick and easy to identify interesting observations among the explanatory variables and interactively discover the differences between these variables. In the current age of “Big Data”, to satisfy the needs of data visualization and modern websites, Shiny is an excellent programming tool which uses simpler coding than traditional web programming.

Keywords:

 

Shiny R Package, Interactive Web Application, Cancer Incidences Data, Data Visualization

References:

 

[1] Ihaka, R. and Gentleman, R.. R: a language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5(3), 299–314.
[2] Paradis E, Claude J, Strimmer K (2004). APE: analyses of phylogenetics and evolution in R language[J]. Bioinformatics, 20(2): 289-290.
[3] R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
[4] Winston Chang (2015). Shiny: Web Application Framework for R. R package version 0.11. http://CRAN.R-project.org/package=Shiny.
[5] Joe Cheng (2015). Introduction to Shiny Applications. LA R Meetup. http://datascience.la/joe-cheng-presents-shiny/.
[6] Surveillance, Epidemiology, and End Results (SEER) Program Research Data (1973-2012), National Cancer Institute, DCCPS, Surveillance Research Program, Surveillance Systems Branch, http://www.seer.cancer.gov.

Citations:

 

APA:
Mudaranthakam, D. P., Liu, J., Karanevich, A., Keighley, J., & Gajewski, B. (2021). A “Shiny” Application: Interactive Online Mapping for the Case Capture Percentages of Expected Cancer Cases in the University of Kansas Cancer Center. Journal of Community Healthcare and Development (JCHD), ISSN: 2652-6026, NADIA, 2(1), 23-30. doi: 10.33832/jchd.2021.2.1.03.

MLA:
Mudaranthakam, Dinesh Pal, et al. “A “Shiny” Application: Interactive Online Mapping for the Case Capture Percentages of Expected Cancer Cases in the University of Kansas Cancer Center.” Journal of Community Healthcare and Development, ISSN: 2652-6025, NADIA, vol. 2, no. 1, 2021, pp. 23-30. JCHD, http://article.nadiapub.com/JCHD/vol2_no1/3.html.

IEEE:
[1] D. P. Mudaranthakam, J. Liu, A. Karanevich, J. Keighley, and B. Gajewski, "A “Shiny” Application: Interactive Online Mapping for the Case Capture Percentages of Expected Cancer Cases in the University of Kansas Cancer Center." Journal of Community Healthcare and Development (JCHD), ISSN: 2652-6025, NADIA, vol. 2, no. 1, pp. 23-30, April 2021.