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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

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Showing 376–400 of 472 papers

TitleStatusHype
Extending the Neural Additive Model for Survival Analysis with EHR Data—0
Factor-Augmented Regularized Model for Hazard Regression—0
Fairness in Survival Analysis: A Novel Conditional Mutual Information Augmentation Approach—0
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models—0
Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets—0
Federated Survival Analysis with Discrete-Time Cox Models—0
FedPseudo: Pseudo value-based Deep Learning Models for Federated Survival Analysis—0
Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications—0
Forecasting Automotive Supply Chain Shortfalls with Heterogeneous Time Series—0
Forecasting from Clinical Textual Time Series: Adaptations of the Encoder and Decoder Language Model Families—0
FPBoost: Fully Parametric Gradient Boosting for Survival Analysis—0
From Non-Paying to Premium: Predicting User Conversion in Video Games with Ensemble Learning—0
From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba—0
Gaussian Processes for Survival Analysis—0
Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacy—0
Generalized Bayesian Ensemble Survival Tree (GBEST) model—0
Global Censored Quantile Random Forest—0
Graph Domain Adaptation with Dual-branch Encoder and Two-level Alignment for Whole Slide Image-based Survival Prediction—0
GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization—0
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
Hazard Gradient Penalty for Survival Analysis—0
High-Dimensional False Discovery Rate Control for Dependent Variables—0
Higher Mediterranean diet score is associated with longer time between relapses in Australian females with multiple sclerosis—0
Hospital transfer risk prediction for COVID-19 patients from a medicalized hotel based on Diffusion GraphSAGE—0
Hybrid Approach of Relation Network and Localized Graph Convolutional Filtering for Breast Cancer Subtype Classification—0
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