Related Experiment Video

Updated: Apr 28, 2026

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury
07:21

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

Published on: May 27, 2022

2.8K

[Application of statistical models for prognostication of outcomes in injured persons with severe trauma]

V V Boĭko, P N Zamiatin, N A Dubrovina

    Klinichna Khirurhiia
    |June 14, 2014
    PubMed

    More Related Videos

    A Contusion Model of Severe Spinal Cord Injury in Rats10:00

    A Contusion Model of Severe Spinal Cord Injury in Rats

    Published on: August 17, 2013

    29.8K
    Establishing a Competing Risk Regression Nomogram Model for Survival Data04:57

    Establishing a Competing Risk Regression Nomogram Model for Survival Data

    Published on: October 23, 2020

    9.9K

    Related Concept Videos

    Introduction To Survival Analysis01:18

    Introduction To Survival Analysis

    Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
    The primary goal of survival analysis is to estimate survival time—the time...
    944
    Comparing the Survival Analysis of Two or More Groups01:20

    Comparing the Survival Analysis of Two or More Groups

    Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
    710
    Parametric Survival Analysis: Weibull and Exponential Methods01:14

    Parametric Survival Analysis: Weibull and Exponential Methods

    Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
    Weibull Distribution
    The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
    1.3K
    Assumptions of Survival Analysis01:15

    Assumptions of Survival Analysis

    Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
    491
    Cancer Survival Analysis01:21

    Cancer Survival Analysis

    Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
    860