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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 211220 of 472 papers

TitleStatusHype
Hazard Gradient Penalty for Survival Analysis0
Hazard function models to estimate mortality rates affecting fish populations with application to the sea mullet (Mugil cephalus) fishery on the Queensland coast (Australia)0
CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis0
GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization0
Copula-Based Deep Survival Models for Dependent Censoring0
Graph Domain Adaptation with Dual-branch Encoder and Two-level Alignment for Whole Slide Image-based Survival Prediction0
Global Censored Quantile Random Forest0
Generalized Bayesian Ensemble Survival Tree (GBEST) model0
Contrastive Learning of Temporal Distinctiveness for Survival Analysis in Electronic Health Records0
Continuous Risk Measures for Driving Support0
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