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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

Showing 126150 of 472 papers

TitleStatusHype
Integrated Machine Learning and Survival Analysis Modeling for Enhanced Chronic Kidney Disease Risk StratificationCode0
Case-Base Neural Networks: survival analysis with time-varying, higher-order interactionsCode0
Heterogeneous Datasets for Federated Survival Analysis SimulationCode0
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing RisksCode0
GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settingsCode0
Cancer Subtype Identification through Integrating Inter and Intra Dataset Relationships in Multi-Omics DataCode0
Calibration Error for Heterogeneous Treatment EffectsCode0
A Multi-Modal Deep Learning Framework for Pan-Cancer PrognosisCode0
Gradient Boosting Survival Tree with Applications in Credit ScoringCode0
Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic informationCode0
SimHawNet: A Modified Hawkes Process for Temporal Network SimulationCode0
Differentially Private Distributed InferenceCode0
HistoKernel: Whole Slide Image Level Maximum Mean Discrepancy Kernels for Pan-Cancer Predictive ModellingCode0
Feature Selection for Survival Analysis with Competing Risks using Deep LearningCode0
BoXHED2.0: Scalable boosting of dynamic survival analysisCode0
Federated Survival ForestsCode0
Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival DataCode0
Binacox: automatic cut-point detection in high-dimensional Cox model with applications in geneticsCode0
Diffsurv: Differentiable sorting for censored time-to-event dataCode0
Flexible Group Fairness Metrics for Survival AnalysisCode0
BoXHED: Boosted eXact Hazard Estimator with Dynamic covariatesCode0
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without DemographicsCode0
Exploring the Wasserstein metric for survival analysisCode0
DNAMite: Interpretable Calibrated Survival Analysis with Discretized Additive ModelsCode0
ALBRT: Cellular Composition Prediction in Routine Histology ImagesCode0
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