Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Receiver Operating Characteristic Plot

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A Single-Dose Bundibugyo Virus Vaccine Protects Macaques Within 3 Days.

bioRxiv : the preprint server for biology·2026

Same author

Quantifying PD1 Saturation by PDL1 in Tumor Tissue Using a Novel RNA Aptamer-Based Assay.

International journal of molecular sciences·2026

Same author

Early Cerebral Edema Subtypes and Functional Outcome in Patients With Cerebral Venous Thrombosis: Insights From the CLOT-VENUS Registry.

Neurology·2026

Same author

Highly efficient anogenital transmission of clade Ia monkeypox virus associated with increased shedding.

Nature communications·2026

Same author

Effects of fipronil bait pellets on two cricetid species: Potential implications for plague mitigation and wildlife conservation.

International journal for parasitology. Parasites and wildlife·2026

Same author

Impact of Comorbidities on Survival among American Indian and Alaska Native People with Cancer: A Surveillance, Epidemiology, and End Results (SEER)-Medicare Study.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology·2026

Search research articles

Related Experiment Video

Updated: Aug 27, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

MATLAB toolbox for ROC analysis of multi-reader multi-case diagnostic imaging studies.

Brian J Smith¹, Stephen L Hillis²

¹Department of Biostatistics, University of Iowa, Iowa City, USA.

Proceedings of Spie--The International Society for Optical Engineering

|September 26, 2022

Summary

This study introduces MRMCaov, a MATLAB toolbox for comparing diagnostic imaging tests using multi-reader, multi-case analysis. It provides robust statistical methods for performance metrics like ROC AUC, aiding in test evaluation.

Keywords:

ANOVA ROC analysis diagnostic radiology multi-reader multi-case software

More Related Videos

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Published on: June 24, 2025

Related Experiment Videos

Last Updated: Aug 27, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Published on: June 24, 2025

Area of Science:

Medical Imaging Analysis
Biostatistics
Radiology Research

Background:

Comparing diagnostic imaging tests requires specialized statistical methods for multi-reader, multi-case studies.
Existing analytical methods can be complex and may not handle overlapping data effectively.

Purpose of the Study:

To introduce the open-source MATLAB MRMCaov toolbox for statistical comparisons of diagnostic tests.
To provide a user-friendly interface for multi-reader multi-case (MRMC) analysis.

Main Methods:

Utilizes analysis of variance methods based on Obuchowski and Rockette, unified by Hillis.
Implements statistical comparisons for reader performance metrics including ROC AUC, sensitivity, and specificity.
Supports various study designs (factorial, nested, partially paired) and inference options (random/fixed readers/cases).

Main Results:

The MRMCaov toolbox offers comprehensive features for MRMC statistical analysis.
It includes estimation of mean performance, confidence intervals, and p-values for test comparisons.
The software supports multiple covariance estimation techniques and is cross-platform compatible.

Conclusions:

MRMCaov provides a powerful and flexible tool for researchers evaluating diagnostic imaging tests.
The toolbox facilitates accurate statistical comparisons of reader performance, enhancing diagnostic test evaluation.