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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

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Showing 151–175 of 472 papers

TitleStatusHype
FedPseudo: Pseudo value-based Deep Learning Models for Federated Survival Analysis—0
A Multi-modal Fusion Framework Based on Multi-task Correlation Learning for Cancer Prognosis Prediction—0
CARMIL: Context-Aware Regularization on Multiple Instance Learning models for Whole Slide Images—0
Dynamic prediction of time to event with survival curves—0
Dynamic Survival Analysis for Early Event Prediction—0
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis—0
Dynamic Survival Transformers for Causal Inference with Electronic Health Records—0
DySurv: dynamic deep learning model for survival analysis with conditional variational inference—0
Distributionally Robust Learning in Survival Analysis—0
Calibrated Predictive Lower Bounds on Time-to-Unsafe-Sampling in LLMs—0
End-Stage Liver Disease Comorbidities in Patients Awaiting Transplantation: Identification and Impact on Liver Transplant Survival—0
End-to-end Multi-source Visual Prompt Tuning for Survival Analysis in Whole Slide Images—0
Discrete Stochastic Models in Continuous Time for Ecology—0
Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis—0
A Deep Active Survival Analysis Approach for Precision Treatment Recommendations: Application of Prostate Cancer—0
Enhancing Federated Survival Analysis through Peer-Driven Client Reputation in Healthcare—0
Fairness in Survival Analysis: A Novel Conditional Mutual Information Augmentation Approach—0
Ensemble Survival Analysis for Preclinical Cognitive Decline Prediction in Alzheimer's Disease Using Longitudinal Biomarkers—0
Churn Prediction in Mobile Social Games: Towards a Complete Assessment Using Survival Ensembles—0
EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, Featuring Prognostic Stratification Boosting—0
Estimating and interpreting secondary attack risk: Binomial considered harmful—0
Estimating Heterogenous Treatment Effects for Survival Data with Doubly Doubly Robust Estimator—0
Estimation of conditional mixture Weibull distribution with right-censored data using neural network for time-to-event analysis—0
Estimation of Time-to-Total Knee Replacement Surgery—0
Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications—0
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