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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 151160 of 472 papers

TitleStatusHype
Gradient Boosting Survival Tree with Applications in Credit ScoringCode0
Dynamical Survival Analysis with Controlled Latent StatesCode0
Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival DataCode0
HistoKernel: Whole Slide Image Level Maximum Mean Discrepancy Kernels for Pan-Cancer Predictive ModellingCode0
Binacox: automatic cut-point detection in high-dimensional Cox model with applications in geneticsCode0
SimHawNet: A Modified Hawkes Process for Temporal Network SimulationCode0
Integrated Machine Learning and Survival Analysis Modeling for Enhanced Chronic Kidney Disease Risk StratificationCode0
Interpretable Machine Learning for Survival AnalysisCode0
Federated Survival ForestsCode0
ALBRT: Cellular Composition Prediction in Routine Histology ImagesCode0
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