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KMWin is a KMplot package developed by Jeremy C. Siek.
KMPlot generates simple 2D and 3D survival plot for Kaplan-Meier survival analysis in R. It is a complete alternative to the KM function of R, and includes all features of the package. (more…)
Kaplan-Meier (KMPlot) is a package with an R function KM() for producing Kaplan-Meier survival curve. KMPlot integrates functions from other packages, namely survminer, ggsurvplot and survcomp, to generate Kaplan-Meier plots and other survival-related graphics.
KMPlot Description:
KMPlot is an R package with functions for creating, manipulating and visualizing Kaplan-Meier survival curves for patient groups. The package provides three R functions: KM(), which creates a Kaplan-Meier plot with survival time on the x-axis, survival status on the y-axis, and patients at risk at the bottom of the plot; KM2Surv() and KM3.surv(), which modify a KM plot by adding a second or third group or patient cohorts; and KM3.pcols(), which combines all columns of a KM plot into a single plot. (more…)
The survival package contains functions for producing survival plots: KMsurv() provides two functions for creating Kaplan-Meier survival plots: KM() is based on the survival R function (see this link for more information) and applies clustering algorithms by groups, it also provides functions for converting the survival data to a log-rank test statistic and plot it against the survival function; KM2Surv() is based on the KMsurv() function and generates a KM plot with groups as an additional feature, and includes an option for plotting survival time as a facet in each group in a 3D KM plot. (more…)
KMSurv is a package for producing Kaplan-Meier survival curves. The package is intended for visualisation purposes and requires the R statistical language and its graphics package. KMSurv allows users to generate Kaplan-Meier survival curves with various options such as specifying different base distributions, levels of cumulative hazard, time intervals, and groups. KM surv gives general solutions in modelling survival data to compare survival curves. (more…)
KIWI is a plotting package for the R graphical environment that allows for the automatic generation of Kaplan-Meier survival plots of data that has been grouped by different key fields. The
KMWin
KMWin supports import and export of data from/to: Excel, Endnote, RIS, MACRO-ENCODED TEXT, CHEMGRAPH, SPSS, MS-Excel, MS-Powerpoint, R-Files (R has to be installed on your server).
It is possible to use different options for graphic and statistical variables, algorithm of estimation survival function, kind of animals included in experiment.
KMWin can save graphs in original form (directory where graphic data are presented) and in PDF form.
KMWin is written in pure C programming language and consists of only one dll file. KMWin does not depend on any additional features of Microsoft Windows operating system.
More than 20 different formats are supported by KMWin.
Relevant information from with this project:
External links:
KMWin Project on Open Source for Windows:
KMWin Project on SourceForge:
KMWin on Google Code:
Directories included in KMWin package:
– KM_Classics_Examples (Directories for examples of KM graphics, all available from KMWin package): KM_Classics_Examples/km_classics_examples
– KMWin.exe (Program which shows how to use KMWin): KMWin/km_win
– KMWin.dll (File which contains KM_Classics_Examples/km_classics_examples directory): KMWin/km_win
– KM_Classics_Examples (Directory which contains graphic examples, all available from KMWin package): KM_Classics_Examples
– KM_Classics_Examples_SW (Directory for source codes of graphic examples): KM_Classics_Examples_SW
Compatible programs:
– ArcGIS
– Filemaker Pro
– MySQL (any version)
– SQLite
– SSMS (SQL Server Management Studio)
– PostgreSQL
– Strawberry Perl
– Ruby
– Windows Scripting Host
Needless to say that KM_Classics_Examples could be used as a reference for a student while investigating KM graphics in R.
License:
The use of the copyrighted works in
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KMWin (Final 2022)
KMWin consists of two parts – a front-end with a user-friendly and a convenient interface, and a back-end with a set of functions for graphic generation of survival curves.
The front-end is implemented by a web application with the help of JavaScript and HTML5. A user-friendly interface allows also to use the application on a smartphone with a browser. The application communicates with a back-end, provided by another Python package, kmeswins. This package is based on the kmeswins library of the R package R2Win.
The application itself is completely open-source and under GPL license. It can be used under Apache License as well.
KMWin Features:
Front-end:
User-friendly HTML5 interface for the application. The application is based on the architecture of the Shiny web application framework and uses JavaScript and HTML5 technologies.
A smartphone interface which uses the same front-end. The application can also be used in a smartphone browser.
A back-end implemented in Python which contains functions to generate survival curves using SPSS, KMPlotter and R2Win packages.
E-mail notifications of the survival analysis if e-mail service is enabled.
Email notifications of the analyzed data if e-mail service is enabled.
Email notifications of the analyzed data if sent by e-mail service is enabled.
If the e-mail is enabled, the survival analysis will be sent by e-mail at the end of the session.
The application is based on the architecture of the Shiny web application framework.
HTML5 technologies: HTML5 File API, Canvas and WebGL support, WebSockets.
Data transfer between server and client. The application provides a REST-based REST API. The data can be transferred using the HTTP POST method, using a file in JSON format or, without transferring any data, in the form of a header.
Libraries and packages used in the project:
Shiny:
SublimeText:
JS-R:
Poppler:
JSXGraph:
R2Win:
Shine:
What’s New in the KMWin?
================
The user interface for KMWin is a.NET Winforms application using the.NET libraries. KMWin is written in C# and can be used on both Microsoft Windows and Linux operating systems (both 32-bit and 64-bit).
Installation:
=============
The latest version of KMWin can be downloaded from its website here:
A full installation involves downloading the.NET SDK and installing KMWin.
Supported Platforms:
====================
KMWin is currently tested for Microsoft Windows operating systems: Windows 98SE, Windows NT 4.0, Windows 2000, Windows XP and Windows Vista. KMWin requires.NET Framework version 3.5 or above.
Compatibility:
==============
KMWin is compatible with R 2.13 and above.
Sample Data Files:
===================
To demonstrate the process of installing, loading, and using KMWin with the examples shown below, please download and install the following datasets:
Sample Usage
============
1. Loading the data
1.1 The example below shows an example where the dataset dat.RData is loaded in the command window.
> iris
Installing / Uninstalling
========================
Please see for details.
Alternate Source:
================
GitHub (release):
If you are new to KMWin and the GPL, you must first have a copy of
KMWin and source code before you use KMWin for the first time.
Therefore, you must either download a copy of KMWin and source code
first, or obtain a license to KMWin through your institution. Then
perform the following simple steps to access KMWin.
1. Download KMWin. (Optional):
System Requirements For KMWin:
Requires a computer with 1 GB RAM and 64 MB video memory.
1080p (HD) graphics.
Requires at least Microsoft Windows 7, Vista, or XP.
Mac (Intel) and Linux (AMD) are supported as well.
Compatible with English, French, Spanish, Italian, and German.
A host of antialiasing and shadow filtering options are available.
Supports both 32-bit and 64-bit editions of Windows.
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