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 126–150 of 472 papers

TitleStatusHype
Deep Learning for Cancer Prognosis Prediction Using Portrait Photos by StyleGAN Embedding—0
An Approach for Clustering Subjects According to Similarities in Cell Distributions within Biopsies—0
A Cost-Aware Approach to Adversarial Robustness in Neural Networks—0
Churn Prediction in Mobile Social Games: Towards a Complete Assessment Using Survival Ensembles—0
Child Care Provider Survival Analysis—0
Analyzing Economic Convergence Across the Americas: A Survival Analysis Approach to GDP per Capita Trajectories—0
Estimation of conditional mixture Weibull distribution with right-censored data using neural network for time-to-event analysis—0
Analyzing Breast Cancer Survival Disparities by Race and Demographic Location: A Survival Analysis Approach—0
A Multiple kernel testing procedure for non-proportional hazards in factorial designs—0
A Deep Learning Approach for Dynamic Survival Analysis with Competing Risks—0
Stop Chasing the C-index: This Is How We Should Evaluate Our Survival Models—0
Estimation of Time-to-Total Knee Replacement Surgery—0
Explainable AI for survival analysis: a median-SHAP approach—0
Causal Inference for Survival Analysis—0
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis—0
A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis—0
CARMIL: Context-Aware Regularization on Multiple Instance Learning models for Whole Slide Images—0
CardioCoT: Hierarchical Reasoning for Multimodal Survival Analysis—0
A Multi-modal Fusion Framework Based on Multi-task Correlation Learning for Cancer Prognosis Prediction—0
EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, Featuring Prognostic Stratification Boosting—0
Enhancing External Validity of Experiments with Ongoing Sampling—0
Enhancing Federated Survival Analysis through Peer-Driven Client Reputation in Healthcare—0
AMMASurv: Asymmetrical Multi-Modal Attention for Accurate Survival Analysis with Whole Slide Images and Gene Expression Data—0
Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis—0
Distributionally Robust Learning in Survival Analysis—0
Show:102550
← PrevPage 6 of 19Next →

No leaderboard results yet.