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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 51–100 of 472 papers

TitleStatusHype
A probabilistic estimation of remaining useful life from censored time-to-event dataCode1
Adversarial Time-to-Event ModelingCode1
AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide ImagesCode1
Discrete-time Competing-Risks Regression with or without PenalizationCode1
Adaptive Sampling for Weighted Log-Rank Survival Trees BoostingCode1
Deep Learning for Survival Analysis: A ReviewCode1
Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing RisksCode1
CDS -- Causal Inference with Deep Survival Model and Time-varying CovariatesCode1
CustOmics: A versatile deep-learning based strategy for multi-omics integrationCode1
Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability GuaranteesCode1
Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modelingCode1
MoME: Mixture of Multimodal Experts for Cancer Survival PredictionCode1
Interpretable machine learning for time-to-event prediction in medicine and healthcareCode1
MIRROR: Multi-Modal Pathological Self-Supervised Representation Learning via Modality Alignment and RetentionCode1
Sensitivity of Survival Analysis MetricsCode1
HEALNet: Multimodal Fusion for Heterogeneous Biomedical DataCode1
CoxKAN: Kolmogorov-Arnold Networks for Interpretable, High-Performance Survival AnalysisCode1
Gradient Boosting Survival Tree with Applications in Credit ScoringCode0
A kernel log-rank test of independence for right-censored dataCode0
SimHawNet: A Modified Hawkes Process for Temporal Network SimulationCode0
Learning Survival Distribution with Implicit Survival FunctionCode0
Adaptive Transformer Modelling of Density Function for Nonparametric Survival AnalysisCode0
Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic informationCode0
Differentially Private Distributed InferenceCode0
A survey of Transformer applications for histopathological image analysis: New developments and future directionsCode0
A Study on Survival Analysis Methods Using Neural Network to Prevent CancersCode0
A General Machine Learning Framework for Survival AnalysisCode0
A General Framework for Visualizing Embedding Spaces of Neural Survival Analysis Models Based on Angular InformationCode0
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCTCode0
GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settingsCode0
A Scalable Discrete-Time Survival Model for Neural NetworksCode0
Adaptive Prototype Learning for Multimodal Cancer Survival AnalysisCode0
A Recurrent Neural Network Survival Model: Predicting Web User Return TimeCode0
Federated Survival ForestsCode0
AdaMHF: Adaptive Multimodal Hierarchical Fusion for Survival PredictionCode0
A novel gradient-based method for decision trees optimizing arbitrary differential loss functionsCode0
Conformalized Survival AnalysisCode0
Computing the Hazard Ratios Associated with Explanatory Variables Using Machine Learning Models of Survival DataCode0
Fairness in Survival Analysis with Distributionally Robust OptimizationCode0
Feature Selection for Survival Analysis with Competing Risks using Deep LearningCode0
Flexible Group Fairness Metrics for Survival AnalysisCode0
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing RisksCode0
Dynamic Survival Analysis for non-Markovian Epidemic ModelsCode0
Energy-based survival modelling using harmoniumsCode0
Dynamical Survival Analysis with Controlled Latent StatesCode0
Conditioning on Time is All You Need for Synthetic Survival Data GenerationCode0
Dynamic Entity-Masked Graph Diffusion Model for histopathological image Representation LearningCode0
Conformalized Survival Distributions: A Generic Post-Process to Increase CalibrationCode0
EOCSA: Predicting Prognosis of Epithelial Ovarian Cancer with Whole Slide Histopathological ImagesCode0
An Efficient Training Algorithm for Kernel Survival Support Vector MachinesCode0
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