Suppr超能文献

一种用于分析多阅读者多病例无反应受试者工作特征研究的新回归方法。

A novel regression method for the analysis of multireader multicase-free-response receiver operating characteristics studies.

机构信息

Department of Biostatistics, School of Public Health, Peking University, Beijing, China.

School of Mathematical Sciences, Peking University, Beijing, China.

出版信息

Stat Med. 2022 Jul 20;41(16):3022-3038. doi: 10.1002/sim.9400. Epub 2022 Apr 5.

Abstract

In diagnostic radiology, the multireader multicase (MRMC) design and the free-response receiver operating characteristics (FROC) method are often used in combination. The cross-correlated data generated by the MRMC-FROC study leads to difficulties in the corresponding analysis, and the need to include covariates in the model further complicates the subsequent analysis. In this paper, we propose a regression approach based on three new measures with good interpretability. The correlation structure of the original test results is taken directly into account in the estimation procedure. The proposed method also allows the inclusion of continuous or discrete covariates. Consistent and asymptotically normal estimators are derived for the new measures. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that the regression approach performs well under a wide range of scenarios. We also apply the proposed regression approach to a diagnostic study of computer-aided diagnosis in lung cancer.

摘要

在诊断放射学中,多读者多病例(MRMC)设计和自由响应接收器操作特性(FROC)方法经常结合使用。MRMC-FROC 研究产生的交叉相关数据导致相应分析困难,并且需要在模型中包含协变量进一步使后续分析复杂化。在本文中,我们提出了一种基于三个具有良好可解释性的新指标的回归方法。在估计过程中直接考虑原始测试结果的相关结构。该方法还允许包含连续或离散协变量。为新指标推导出一致和渐近正态的估计量。进行了模拟研究以评估所提出方法的性能。模拟结果表明,该回归方法在广泛的场景下表现良好。我们还将所提出的回归方法应用于肺癌计算机辅助诊断的诊断研究中。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验