easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment
By Dincer Goksuluk, Selçuk Korkmaz, Gokmen Zararsiz, Ahmet Ergun Karaagaoglu. The R Journal, 2016
361 citations recorded by the source corpus.
ROC curve analysis is a fundamental tool for evaluating the performance of a marker in a number of research areas, e.g., biomedicine, bioinformatics, engineering etc., and is frequently used for discriminating cases from controls. There are a number of analysis tools which are used to guide researchers through their analysis. Some of these tools are commercial and provide basic methods for ROC curve analysis while others offer advanced analysis techniques and a command-based user interface, such as the R environment. The R environmentg includes comprehensive tools for ROC curve analysis; however, using a command-based interface might be challenging and time consuming when a quick evaluation is desired; especially for non-R users, physicians etc. Hence, a quick, comprehensive, free and easy-to-use analysis tool is required. For this purpose, we developed a user-friendly webtool based on the R language. This tool provides ROC statistics, graphical tools, optimal cutpoint calculation, comparison of several markers, and sample size estimation to support researchers in their decisions without writing R codes. easyROC can be used via any device with an internet connection independently of the operating system. The web interface of easyROC is constructed with the R package shiny. This tool is freely available through www.biosoft.hacettepe.edu.tr/easyROC.
Subfields: Artificial Intelligence, Environmental Engineering, Health Information Management
View Paper: https://www.semanticscholar.org/paper/5b4bb045382c9ffbb13afa61d3f5bce03fe531c0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Environmental Engineering
In Health Information Management
Citations in the corpus
- Receiver operating characteristic curve: overview and practical use for clinicians (2022, methodology): “The web tool for the ROC curve analysis based on R, which includes easyROC and plotROC [33,34], is a web-based application that uses the R packages plyr, pROC, and OptimalCutpoints to perform ROC curve analyses, extending the functions of multiple ROC packages in R so that researchers can perform RO”
- Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation (2021, neutral): “A few representative examples used in these tools in medical research include an online calculator for receiver operator characteristics [3], a tool to determine optimal cut-off values for clinical tests [4], and a sample size calculator for randomized clinical trials [5].”