pROC: an open-source package for R and S+ to analyze and compare ROC curves
Xavier Robin,Natacha Turck,Alexandre Hainard,Natalia Tiberti,Frédérique Lisacek,Jean-Charles Sanchez,Markus Müller +6 more
TLDR
pROC as mentioned in this paper is a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface.Abstract:
Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/
under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.read more
Citations
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Journal ArticleDOI
Predictors of Outcome in Traumatic Brain Injury: New Insight Using Receiver Operating Curve Indices and Bayesian Network Analysis.
TL;DR: In this article, the authors established importance ranking for outcome predictors based on receiver operating indices to identify key predictors of outcome and create simple predictive models, and explored the associations between key outcome predictor using Bayesian networks to gain further insight into predictor importance.
Journal ArticleDOI
New data shed light on Y-loss-related pathogenesis in myelodysplastic syndromes.
Christina Ganster,Dietrich Kämpfe,Klaus Jung,Friederike Braulke,Katayoon Shirneshan,Sigrid Machherndl-Spandl,Susanne Suessner,Carsten P. Bramlage,Tobias J. Legler,Michael Koziolek,Detlef Haase,Julie Schanz +11 more
TL;DR: It is concluded that LOY is clonal in a substantial number of MDS based on an age‐related predisposition and a threshold between age‐ and disease‐associated LOY in MDS is defined.
Journal ArticleDOI
DNA from fecal immunochemical test can replace stool for detection of colonic lesions using a microbiota-based model
TL;DR: The potential for using residual buffer from FIT cartridges in place of stool for microbiota-based screening for CRC is demonstrated and this may reduce the need to collect and process separate stool samples and may facilitate combining FIT and microbiota- based biomarkers into a single test.
Journal ArticleDOI
Serum phosphatidylethanolamine levels distinguish benign from malignant solitary pulmonary nodules and represent a potential diagnostic biomarker for lung cancer.
Johannes F. Fahrmann,Dmitry Grapov,Brian C. DeFelice,Sandra L. Taylor,Kyoungmi Kim,Karen Kelly,William R. Wikoff,Harvey I. Pass,William N. Rom,Oliver Fiehn,Oliver Fiehn,Suzanne Miyamoto +11 more
TL;DR: Evidence of early metabolic alterations that can possibly distinguish malignant from benign SPNs is demonstrated, and further studies in larger pools of samples are warranted.
Journal ArticleDOI
In Reply: White Blood Cell Count Improves Prediction of Delayed Cerebral Ischemia Following Aneurysmal Subarachnoid Hemorrhage.
Fawaz Al-Mufti,Kalina Anna Misiolek,David Roh,Aws Alawi,Andrew Bauerschmidt,Soojin Park,Sachin Agarwal,Philip M. Meyers,E. Sander Connolly,Jan Claassen,J. Michael Schmidt +10 more
TL;DR: Good- grade patients with early elevations in WBC count have a similar risk and hazard for DCI as poor-grade patients and may be candidates to be safely downgraded from the intensive care unit, leading to cost savings for both patient families and hospitals.
References
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