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Survival Analysis

Survival Analysis is a branch of statistics focused on the study of time-to-event data, usually called survival times. This type of data appears in a wide range of applications such as failure times in mechanical systems, death times of patients in a clinical trial or duration of unemployment in a population. One of the main objectives of Survival Analysis is the estimation of the so-called survival function and the hazard function. If a random variable has density function $f$ and cumulative distribution function $F$, then its survival function $S$ is $1-F$, and its hazard $λ$ is $f/S$.

Source: Gaussian Processes for Survival Analysis

Image: Kvamme et al.

Papers

Showing 451460 of 472 papers

TitleStatusHype
WSISA: Making Survival Prediction From Whole Slide Histopathological Images0
Natural mortality of Trachurus novaezelandiae and their size selection by purse seines off south-eastern Australia0
Deep Learning for Patient-Specific Kidney Graft Survival AnalysisCode0
Contextual Explanation NetworksCode0
Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors0
Playtime Measurement with Survival Analysis0
Identification of Cancer Patient Subgroups via Smoothed Shortest Path Graph Kernel0
An Efficient Training Algorithm for Kernel Survival Support Vector MachinesCode0
Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets0
Gaussian Processes for Survival Analysis0
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