相关实验视频

Updated: Jan 25, 2026

A Mouse Model for Pathogen-induced Chronic Inflammation at Local and Systemic Sites
09:52

A Mouse Model for Pathogen-induced Chronic Inflammation at Local and Systemic Sites

Published on: August 8, 2014

18.1K

一个基于全身性炎症的新型模型,用于预测HBV相关ACLF的死亡率

Wenting Peng1, Jiao Yuan1, Shifang Peng1

  • 1Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, China.

Journal of medical virology
|January 24, 2026
PubMed
概括

对淋巴细胞的C-反应蛋白比率 (CLR) 是乙型肝炎病毒 (HBV) 相关的急性至慢性肝衰竭 (ACLF) 糟糕结果的显著预测因素. 这种炎症标志物有助于识别高风险患者,以便更好地管理.

关键词:
C-反应性蛋白与淋巴细胞的比例.急性-慢性肝功能衰竭之间存在差异.预测模型是一个预测模型.这是一个渐进的过程.幸存率 幸存率 生存率

更多相关视频

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

500
A Protocol for Computer-Based Protein Structure and Function Prediction16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

69.7K

相关概念视频

Inflammation01:38

Inflammation

Overview
61.9K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries
45.6K
Prediction Intervals01:03

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
3.3K
Second Order systems II01:18

Second Order systems II

In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
396
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
1.2K
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

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...
1.2K