LinkR is a web application that allows for visualization and analysis of healthcare data.
The application is coded in R using the Shiny library. It uses the common data model OMOP.
The application is for:
- healthcare professionals, an intuitive interface allows healthcare professionals to analyze data and conduct research projects without advanced programming knowledge
- data scientists and statisticians, LinkR provides access to a full R and Python environment, allowing data scientists and statisticians to exploit all the features of advanced data analysis
Thus, LinkR facilitates collaborative work.
Below are some of the key features that make LinkR a powerful tool for healthcare data analysis.
Easily create a custom patient record tailored to the specific needs
of your research project.
As you switch between patients, the
figures dynamically update to reflect each patient’s specific data.
Create customized dashboards to easily explore your data.
Use
an intuitive graphical interface to visualize aggregated patient
data.
Generate and, if required, modify the
corresponding R or Python code directly from the figures you create.
Organize your projects into tabs. Decide which data to display and in what format.
“I’d like to display respiratory rate and saturation as a timeline”
LinkR is an open source application.
It contributes to open science by allowing the sharing of:
- projects: import and export your projects in one click, reproduce projects with your own data
- scripts: share interoperable scripts, thanks to the use of the common OMOP data model
- plugins: help improve the application by creating plugins and sharing them
The remotes library must be installed, you can install it with:
install.packages("remotes")You can install the development version from Framagit, with:
remotes::install_gitlab("interhop/linkr/linkr", host = "framagit.org")IMPORTANT: The application requires version 0.3.0 of shiny.fluent. By default, version 0.4.0 is installed, which has unresolved bugs.
You can install version 0.3.0 with:
remotes::install_github('Appsilon/shiny.fluent', ref = 'dd1c956')To launch the Shiny app, run:
linkr::linkr(language = "en")See ?linkr::linkr for more informations.
Visit our website for further details.
LinkR thrives on community support to grow and improve! You can contribute by developing plugins, enhancing the application’s codebase, or reporting bugs to help us maintain and refine the application.
Tackle open issues: Join us in addressing challenges by visiting our issue tracker.
Report bugs: If you encounter a bug, please let us know by creating a detailed report on the issue tracker.
LinkR is supported by the Interhop association, which advocates for open-source solutions and interoperability in healthcare.
You can help advance open science in healthcare by contributing to LinkR’s development. Consider making a donation to support our mission.
Email: [email protected].