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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 191200 of 472 papers

TitleStatusHype
Differentially Private Distributed InferenceCode0
Online Learning Approach for Survival Analysis0
OPSurv: Orthogonal Polynomials Quadrature Algorithm for Survival Analysis0
Explainable AI for survival analysis: a median-SHAP approach0
Dynamical Survival Analysis with Controlled Latent StatesCode0
High-Dimensional False Discovery Rate Control for Dependent Variables0
Optimal Sparse Survival TreesCode0
SCANIA Component X Dataset: A Real-World Multivariate Time Series Dataset for Predictive Maintenance0
Survival Analysis of Young Triple-Negative Breast Cancer Patients0
TripleSurv: Triplet Time-adaptive Coordinate Loss for Survival AnalysisCode0
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