Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

569
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...
569
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

1.7K
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
1.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Machine learning for predicting institutionalization and mortality risks among older home care recipients with routinely collected need assessment data: explainable AI for long-term care.

BMC medical informatics and decision making·2026
Same author

Causal Inference in the Presence of Missing Outcome and Treatment Variables: Triply Robust Estimator and Sensitivity Analysis.

Statistics in medicine·2026
Same author

Robust Estimation of Population Attributable Fractions in the Presence of Multiple Ordered Mediators.

Statistics in medicine·2026
Same author

Response to: 'Methodological considerations in the analysis of time-to-event outcomes with MAIHDA' by Bashir and Al-Kassab-Córdova.

Journal of epidemiology and community health·2026
Same author

Abdominopelvic computed tomography during pregnancy and the risk of congenital malformations: protocol for a nationwide population-based cohort study in South Korea.

BMJ open·2026
Same author

On the robustness of truncated negative binomial regression model: application to field epidemiology.

Journal of applied statistics·2026

相关实验视频

Updated: Mar 18, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.1K

评估二进制医学测试的诊断准确性 在多读器多个案例研究中的二进制医学测试

Seungjae Lee1,2, Sowon Jang3, Woojoo Lee2,4

  • 1Department of Applied Statistics, Kyonggi University, Suwon, Republic of Korea.

Statistics in medicine
|March 17, 2026
PubMed
概括

多个读者多个案例 (MRMC) 研究比较诊断性能. 条件后勤回归为复杂的MRMC数据提供了强大的分析方法,改善了灵敏度和特异性比较.

关键词:
科克兰的 科克兰的这是McNemar的测试.二元诊断测试二元诊断测试有条件的逻辑回归.多个阅读器多个案例.灵敏度和特异性 灵敏度和特异性

更多相关视频

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
09:00

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

1.3K
Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
05:58

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Published on: March 22, 2022

4.6K

相关实验视频

Last Updated: Mar 18, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.1K
Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
09:00

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

1.3K
Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
05:58

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Published on: March 22, 2022

4.6K

科学领域:

  • 医学成像分析分析 医学成像分析
  • 生物统计学 生物统计学
  • 诊断测试评价 诊断测试评价 诊断测试评价

背景情况:

  • 多读者多病例 (MRMC) 研究对于评估医疗诊断性能至关重要.
  • 分析MRMC数据中的复杂相关性存在重大挑战.
  • 通常使用的方法包括一般化的估计方程,一般化的线性混合模型和McNemar的测试.

研究的目的:

  • 解释MRMC研究条件逻辑回归的理论特性.
  • 探索条件逻辑回归,科克兰的Q和麦克内马尔的测试之间的关系.
  • 为在MRMC环境中比较诊断性能提供强大的分析方法.

主要方法:

  • 对MRMC数据应用条件逻辑回归的理论解释.
  • 探索统计属性和与现有测试的关系.
  • 为了验证该方法,进行了广泛的模拟研究和现实数据分析.

主要成果:

  • 条件后勤回归为MRMC分析提供了一个理论上健全的框架.
  • 条件逻辑回归与已确定的统计测试之间的证明关系.
  • 通过模拟和真实数据验证拟议方法的性能.

结论:

  • 条件后勤回归是分析MRMC研究的一个有价值的工具.
  • 这种方法增强了跨成像模式的灵敏度和特异性的比较.
  • 该研究提供了一种更强大的方法来处理诊断绩效评估中的复杂相关性.