SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 421–430 of 472 papers

TitleStatusHype
Long-Term Pipeline Failure Prediction Using Nonparametric Survival Analysis—0
Modeling Long Sequences in Bladder Cancer Recurrence: A Comparative Evaluation of LSTM,Transformer,and Mamba—0
Machine Learning for Survival Analysis: A Survey—0
Masked Clinical Modelling: A Framework for Synthetic and Augmented Survival Data Generation—0
MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks—0
Maximum Likelihood Estimation of Flexible Survival Densities with Importance Sampling—0
Medical World Model: Generative Simulation of Tumor Evolution for Treatment Planning—0
Metaparametric Neural Networks for Survival Analysis—0
mlr3proba: An R Package for Machine Learning in Survival Analysis—0
Modeling 3D cardiac contraction and relaxation with point cloud deformation networks—0
Show:102550
← PrevPage 43 of 48Next →

No leaderboard results yet.