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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 241250 of 472 papers

TitleStatusHype
A General Framework for Visualizing Embedding Spaces of Neural Survival Analysis Models Based on Angular InformationCode0
Proper Scoring Rules for Survival AnalysisCode0
Diffsurv: Differentiable sorting for censored time-to-event dataCode0
Interpretable (not just posthoc-explainable) heterogeneous survivor bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions0
Using Geographic Location-based Public Health Features in Survival AnalysisCode0
Searching for the "Holy Grail" of sponsorship-linked marketing: A generalizable sponsorship ROI model0
Une comparaison des algorithmes d'apprentissage pour la survie avec données manquantes0
CLSA: Contrastive Learning-based Survival Analysis for Popularity Prediction in MEC Networks0
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study0
Continuous Risk Measures for Driving Support0
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