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 291–300 of 472 papers

TitleStatusHype
Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered care—0
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study—0
A Latent Space Model for HLA Compatibility Networks in Kidney Transplantation—0
A meaningful prediction of functional decline in amyotrophic lateral sclerosis based on multi-event survival analysis—0
AMMASurv: Asymmetrical Multi-Modal Attention for Accurate Survival Analysis with Whole Slide Images and Gene Expression Data—0
A Multi-modal Fusion Framework Based on Multi-task Correlation Learning for Cancer Prognosis Prediction—0
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis—0
A Multiple kernel testing procedure for non-proportional hazards in factorial designs—0
Analyzing Breast Cancer Survival Disparities by Race and Demographic Location: A Survival Analysis Approach—0
Analyzing Economic Convergence Across the Americas: A Survival Analysis Approach to GDP per Capita Trajectories—0
Show:102550
← PrevPage 30 of 48Next →

No leaderboard results yet.