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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 101–150 of 472 papers

TitleStatusHype
A novel gradient-based method for decision trees optimizing arbitrary differential loss functionsCode0
Ensemble Survival Analysis for Preclinical Cognitive Decline Prediction in Alzheimer's Disease Using Longitudinal Biomarkers—0
Generalized Bayesian Ensemble Survival Tree (GBEST) model—0
Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event DataCode0
Attention-Based Synthetic Data Generation for Calibration-Enhanced Survival Analysis: A Case Study for Chronic Kidney Disease Using Electronic Health Records—0
Adaptive Prototype Learning for Multimodal Cancer Survival AnalysisCode0
Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis—0
Overcoming Dependent Censoring in the Evaluation of Survival ModelsCode0
Enhancing External Validity of Experiments with Ongoing Sampling—0
Censor Dependent Variational InferenceCode0
4D VQ-GAN: Synthesising Medical Scans at Any Time Point for Personalised Disease Progression Modelling of Idiopathic Pulmonary Fibrosis—0
CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learningCode0
Fairness in Survival Analysis: A Novel Conditional Mutual Information Augmentation Approach—0
Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel ImagesCode0
Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift—0
A Multi-Modal Deep Learning Framework for Pan-Cancer PrognosisCode0
Improved joint modelling of breast cancer radiomics features and hazard by image registration aided longitudinal CT data—0
Survival Analysis Revisited: Understanding and Unifying Poisson, Exponential, and Cox Models in Fall Risk Analysis—0
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis—0
SurvAttack: Black-Box Attack On Survival Models through Ontology-Informed EHR Perturbation—0
From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba—0
Dynamic Entity-Masked Graph Diffusion Model for histopathological image Representation LearningCode0
Doubly Robust Conformalized Survival Analysis with Right-Censored DataCode0
SurvBETA: Ensemble-Based Survival Models Using Beran Estimators and Several Attention MechanismsCode0
Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered care—0
A Differentially Private Kaplan-Meier Estimator for Privacy-Preserving Survival Analysis—0
A Versatile Influence Function for Data Attribution with Non-Decomposable Loss—0
EsurvFusion: An evidential multimodal survival fusion model based on Gaussian random fuzzy numbers—0
Enhanced Lung Cancer Survival Prediction using Semi-Supervised Pseudo-Labeling and Learning from Diverse PET/CT Datasets—0
RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency—0
Graph Domain Adaptation with Dual-branch Encoder and Two-level Alignment for Whole Slide Image-based Survival Prediction—0
Integrated Machine Learning and Survival Analysis Modeling for Enhanced Chronic Kidney Disease Risk StratificationCode0
Evidential time-to-event prediction with calibrated uncertainty quantification—0
DNAMite: Interpretable Calibrated Survival Analysis with Discretized Additive ModelsCode0
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models—0
Masked Clinical Modelling: A Framework for Synthetic and Augmented Survival Data Generation—0
Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks—0
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing RisksCode0
Predicting Breast Cancer Survival: A Survival Analysis Approach Using Log Odds and Clinical Variables—0
Global Censored Quantile Random Forest—0
End-Stage Liver Disease Comorbidities in Patients Awaiting Transplantation: Identification and Impact on Liver Transplant Survival—0
Toward a Well-Calibrated Discrimination via Survival Outcome-Aware Contrastive Learning—0
Deep End-to-End Survival Analysis with Temporal Consistency—0
SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Network—0
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCTCode0
Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling—0
FPBoost: Fully Parametric Gradient Boosting for Survival Analysis—0
SeqRisk: Transformer-augmented latent variable model for improved survival prediction with longitudinal data—0
A Cost-Aware Approach to Adversarial Robustness in Neural Networks—0
Adaptive Transformer Modelling of Density Function for Nonparametric Survival AnalysisCode0
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