MRMCsamplesize: An R Package for Estimating Sample Sizes for Multi-Reader Multi-Case Studies

Author:

Robert DennisORCID,Sathyamurthy Saigopal,Putha Preetham

Abstract

AbstractMulti-Reader Multi-Case (MRMC) studies are typically used to evaluate improvement in diagnostic accuracy of readers (diagnosticians) when they are assisted by a computer-assisted device (CAD) such as, but not limited to, those based on Artificial Intelligence (AI) algorithms. Statistical analysis of MRMC study data is not trivial and these studies can consume a lot of resources. Optimal planning is crucial and estimation of sample size is a significant step during the study planning phase. MRMC sample size estimations require many parameter assumptions and without pilot data this is generally not intuitive. MRMCsamplesize package can help researchers to estimate sample sizes for an MRMC study in the absence of any pilot data. The program outputs the number of cases required for a given number of readers. The package can also estimate sample sizes for scenarios where intra-cluster correlation (ICC) needs to be adjusted.

Publisher

Cold Spring Harbor Laboratory

Reference18 articles.

1. Bounding sample size projections for the area under a ROC curve

2. CDRH. 2022. “Clinical Performance Assessment CADe 510(k) Submissions Guidance.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/clinical-performance-assessment-considerations-computer-assisted-detection-devices-applied-radiology.

3. Chakraborty, Dev , and Xuetong Zhai . 2023. RJafroc: Artificial Intelligence Systems and Observer Performance. https://dpc10ster.github.io/RJafroc/.

4. Receiver Operating Characteristic Rating Analysis

5. FDA. 2023. “AI/ML Enabled Medical Devices.” https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3