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

Showing 161170 of 472 papers

TitleStatusHype
SAVAE: Leveraging the variational Bayes autoencoder for survival analysisCode0
MixEHR-SurG: a joint proportional hazard and guided topic model for inferring mortality-associated topics from electronic health recordsCode0
ICTSurF: Implicit Continuous-Time Survival Functions with Neural NetworksCode0
Composite Survival Analysis: Learning with Auxiliary Aggregated Baselines and Survival Scores0
Cancer Subtype Identification through Integrating Inter and Intra Dataset Relationships in Multi-Omics DataCode0
Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic informationCode0
SurvTimeSurvival: Survival Analysis On The Patient With Multiple Visits/RecordsCode0
HEALNet: Multimodal Fusion for Heterogeneous Biomedical DataCode1
Clinical Characteristics and Laboratory Biomarkers in ICU-admitted Septic Patients with and without Bacteremia0
Likelihood Ratio Confidence Sets for Sequential Decision Making0
Show:102550
← PrevPage 17 of 48Next →

No leaderboard results yet.