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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 341350 of 472 papers

TitleStatusHype
The structure of online social networks modulates the rate of lexical changeCode0
BoXHED2.0: Scalable boosting of dynamic survival analysisCode0
BERTSurv: BERT-Based Survival Models for Predicting Outcomes of Trauma Patients0
Conformalized Survival AnalysisCode0
Predicting Kidney Transplant Survival using Multiple Feature Representations for HLAs0
Exploring the Wasserstein metric for survival analysisCode0
The Expediting Effect of Monitoring on Infrastructural Works. A Regression-Discontinuity Approach with Multiple Assignment Variables0
Variational Bayes survival analysis for unemployment modelling0
Computing the Hazard Ratios Associated with Explanatory Variables Using Machine Learning Models of Survival DataCode0
Dynamic prediction of time to event with survival curves0
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