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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 91100 of 472 papers

TitleStatusHype
Forecasting from Clinical Textual Time Series: Adaptations of the Encoder and Decoder Language Model Families0
Predicting the Lifespan of Industrial Printheads with Survival Analysis0
ICBM community cancer registry analysis: a focus on Non-Hodgkin Lymphoma cases in missileers0
Interpretable Non-linear Survival Analysis with Evolutionary Symbolic RegressionCode0
Vision Transformers with Autoencoders and Explainable AI for Cancer Patient Risk Stratification Using Whole Slide Imaging0
Extending Cox Proportional Hazards Model with Symbolic Non-Linear Log-Risk Functions for Survival AnalysisCode0
Improving Diseases Predictions Utilizing External Bio-Banks0
AdaMHF: Adaptive Multimodal Hierarchical Fusion for Survival PredictionCode0
Interpretable Deep Regression Models with Interval-Censored Failure Time Data0
VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic ReconstructionCode0
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