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
Protein oxidation, nitration and glycation biomarkers for early-stage diagnosis of osteoarthritis of the knee and typing and progression of arthritic disease.
Usman Ahmed,Attia Anwar,Richard S. Savage,Paul J. Thornalley,Paul J. Thornalley,Naila Rabbani,Naila Rabbani +6 more
TL;DR: Oxidized, nitrated and glycated amino acids combined with hydroxyproline and anti-CCP antibody status provided a plasma-based biochemical test of relatively high sensitivity and specificity for early-stage diagnosis and typing of arthritic disease.
Journal ArticleDOI
Predicting two-year survival versus non-survival after first myocardial infarction using machine learning and Swedish national register data
TL;DR: Improved mortality prediction at hospital discharge after first MI is important for identifying high-risk individuals eligible for intensified treatment and care and because of the superior national coverage, the best model can potentially be used to better differentiate new patients, allowing for improved targeting of limited resources.
Journal ArticleDOI
Neuroimaging-Based Classification Algorithm for Predicting 1p/19q-Codeletion Status in IDH-Mutant Lower Grade Gliomas.
Prem P. Batchala,Thomas Jose Eluvathingal Muttikkal,Joseph Donahue,James T. Patrie,David Schiff,Camilo E. Fadul,E.K. Mrachek,M.-B. Lopes,Rajan Jain,Sohil H. Patel +9 more
TL;DR: A classification algorithm based on simple, reproducible neuroimaging metrics and patient age that demonstrates a moderate prediction accuracy of 1p/19q-codeletion status among IDH-mutant lower grade gliomas is validated.
Journal ArticleDOI
The NOVA Score: A Proposal to Reduce the Need for Transesophageal Echocardiography in Patients With Enterococcal Bacteremia
Emilio Bouza,Martha Kestler,Martha Kestler,Teresa Beca,Gabriel Mariscal,Marta Rodríguez-Créixems,Javier Bermejo,Javier Bermejo,Ana Fernández-Cruz,Francisco Fernández-Avilés,Francisco Fernández-Avilés,Patricia Muñoz +11 more
TL;DR: Depending on local prevalence of endocarditis, application of the NOVA score may safely obviate echocardiography in 14%-27% of patients with E-BSI and that TEE could be obviated.
Journal ArticleDOI
Development of an Objective Autism Risk Index Using Remote Eye Tracking
Thomas W. Frazier,Eric W. Klingemier,Mary Beukemann,Leslie Speer,Leslie A. Markowitz,Sumit Parikh,Steven Wexberg,Kimberly Giuliano,Elaine Schulte,Carol Delahunty,Veena Ahuja,Charis Eng,Michael J. Manos,Antonio Y. Hardan,Eric A. Youngstrom,Mark S. Strauss +15 more
TL;DR: The autism risk index may be a useful quantitative and objective measure of risk for autism in at-risk settings if validated and scaled for clinical use, and could inform clinical judgment regarding ASD diagnosis and track symptom improvements.
References
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