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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 161170 of 472 papers

TitleStatusHype
Censor Dependent Variational InferenceCode0
GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settingsCode0
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCTCode0
ALBRT: Cellular Composition Prediction in Routine Histology ImagesCode0
Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic informationCode0
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing RisksCode0
Deep Recurrent Survival AnalysisCode0
Feature Selection for Survival Analysis with Competing Risks using Deep LearningCode0
Deep Neural Networks for Survival Analysis Based on a Multi-Task FrameworkCode0
Fairness in Survival Analysis with Distributionally Robust OptimizationCode0
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