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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 176200 of 472 papers

TitleStatusHype
Avoiding C-hacking when evaluating survival distribution predictions with discrimination measuresCode0
Clustering Survival Data using a Mixture of Non-parametric ExpertsCode0
Reinterpreting survival analysis in the universal approximator ageCode0
An Efficient Training Algorithm for Kernel Survival Support Vector MachinesCode0
SAFE: A Neural Survival Analysis Model for Fraud Early DetectionCode0
Deep Recurrent Survival AnalysisCode0
Exploring the Wasserstein metric for survival analysisCode0
Differentially Private Distributed InferenceCode0
GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settingsCode0
Deep Neural Networks for Survival Analysis Based on a Multi-Task FrameworkCode0
SimHawNet: A Modified Hawkes Process for Temporal Network SimulationCode0
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing RisksCode0
A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional DataCode0
Structured Learning in Time-dependent Cox ModelsCode0
Feature Selection for Survival Analysis with Competing Risks using Deep LearningCode0
Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic informationCode0
Deep Learning for Patient-Specific Kidney Graft Survival AnalysisCode0
Efficient Training of Probabilistic Neural Networks for Survival AnalysisCode0
Gradient Boosting Survival Tree with Applications in Credit ScoringCode0
Interpretable Machine Learning for Survival AnalysisCode0
Flexible Group Fairness Metrics for Survival AnalysisCode0
MPVNN: Mutated Pathway Visible Neural Network Architecture for Interpretable Prediction of Cancer-specific Survival RiskCode0
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCTCode0
Deep Learning for Cancer Prognosis Prediction Using Portrait Photos by StyleGAN Embedding0
Deep Learning Approach for Predicting 30 Day Readmissions after Coronary Artery Bypass Graft Surgery0
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