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Survival Analysis Paper List

A list of papers/resources in Survival Analysis that I have read or would like to read. Should you wish to suggest an addition to this list, please feel free to open an issue or pull request.

Last Update Time: 2025.06.07

*Please note that some papers may belong to multiple categories. However, I've organized them according to their most significant contribution (purely subjective).

Tutorials and Surveys

Title Publisher Date Code Notes
Machine Learning for Survival Analysis: A Survey ACM Computing Surveys 2019.02 Slides
Calibration: the Achilles heel of predictive analytics BMC Medicine 2019.12
A tutorial on calibration measurements and calibration models for clinical prediction models JAMIA 2020.02 R
Survival analysis—time-to-event data and censoring Nature Methods 2022.04
Survey: Strategies for Loss-Based Discrete-Time Hazard and Survival Function Estimation ICTC 2022.10
Regression modeling of time-to-event data with censoring Nature Methods 2022.11
Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures Bioinformatics 2022.09
Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review Lancet Digital Health 2024.02
Deep learning for survival analysis: a review Artificial Intelligence Review 2024.02
Review of Language Models for Survival Analysis AAAI Sring Symposium on Clinical FMs 2024.05 PyTorch
An Introduction to Deep Survival Analysis Models for Predicting Time-to-Event Outcomes Foundation and Trends in Machine Learning 2024.10 PyTorch
Beyond Cox Models: Assessing the Performance of Machine-Learning Methods in Non-Proportional Hazards and Non-Linear Survival Analysis ArXiv 2025.04 PyTorch

Perspective and Opinion

Title Publisher Date
Why Test for Proportional Hazards JAMA 2020.03
Stop Chasing the C-index: This Is How We Should Evaluate Our Survival Models Arxiv 2025.06

ML and DL for Survival Analysis

Keyword Title Publisher Date Code Notes
GBMCOX The State of Boosting Computing Science and Statistics 2008 R
RSF Random Survival Forest The Annals of Applied Statistics 2008 R
MTLR Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors NeurIPS 2011 R Poster
DSA Deep Survival Analysis ML4HC 2016
N-MTLR Deep Neural Networks for Survival Analysis Based on a Multi-Task Framework Arxiv 2018.01 Python
DeepSurv DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network BMC Medical Research Methodology 2018.02 Python
DATE & DRAFT Adversarial Time-to-Event Modeling ICML 2018.07 TensorFlow
CoxTime / CoxCC Time-to-Event Prediction with Neural Networks and Cox Regression JMLR 2019.08 PyTorch PyCox 1-3
PCHazard / LogisticHazard Continuous and Discrete-Time Survival Prediction with Neural Networks Arxiv 2019.10 PyTorch PyCox 2-3
SurvivalQuilts Temporal Quilting for Survival Analysis AISTATS 2020.04 Python
SCA Survival Cluster Analysis ACM CHIL 2020.04 TensorFlow
VAECox Improved survival analysis by learning shared genomic information from pan-cancer data Bioinformatics 2020.07 Pytorch
DCM Deep Cox Mixtures for Survival Regression NeurIPS Machine Learning for Health Workshop 2021.01 TensorFlow
DHBN Using Discrete Hazard Bayesian Networks to Identify which Features are Relevant at each Time in a Survival Prediction Model AAAI Spring Symposium (SP-ACA) 2021.03 R
TDSA Transformer-Based Deep Survival Analysis AAAI Spring Symposium (SP-ACA) 2021.03
DeepQuantreg Deep learning for quantile regression under right censoring: DeepQuantreg Computational Statistics and Data Analysis 2021.07 TensorFlow
IWSG Inverse-Weighted Survival Games NeurIPS 2021.12 PyTorch
DeepEH Deep Extended Hazard Models for Survival Analysis NeurIPS 2021.12
VaDeSC A Deep Variational Approach to Clustering Survival Data ICLR 2022.03 TensorFlow
ODE-Cox Survival Analysis via Ordinary Differential Equations JASA 2022
DeSurv Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival Analysis AIStats 2022.05 PyTorch
Survival MDN Survival Mixture Density Networks ML4HC 2022.05 PyTorch
SODEN SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks JMLR 2022 PyTorch
DCS Deep Learning-Based Discrete Calibrated Survival Prediction ICDH 2022.08 PyTorch
CQRNN Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis NeurIPS 2022.11 PyTorth Poster
MSSDA Multi-Source Survival Domain Adaptation AAAI 2023
DH-MNN Metaparametric Neural Networks for Survival Analysis TNNLS 2023.08
NSOTree Neural Survival Oblique Tree Arxiv 2023.09 Python
NNCDE Conditional Distribution Function Estimation Using Neural Networks for Censored and Uncensored Data JMLR 2023.12 PyTorch
NFM Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions NeurIPS 2023.12 PyTorch
Diffsurv Differentiable sorting for censored time-to-event data NeurIPS 2023.12 PyTorch
OSST Optimal Sparse Survival Trees AIStats 2024.01 Python
Survival Kernets Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee JMLR 2024.02 Pytorch
deepAFT deepAFT: A nonlinear accelerated failure time model with artificial neural network Statistics in Medicine 2024.06 R
SurvReLU Inherently Interpretable Survival Analysis via Deep ReLU Networks CIKM 2024.07 Code
FastSurvival FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models NeurIPS 2024.10
ConSurv Toward a Well-Calibrated Discrimination via Survival Outcome-Aware Contrastive Learning NeurIPS 2024.10 PyTorch
L2Boost-CUT / L2Boost-IMP Boosting Methods for Interval-censored Data with Regression and Classification ICLR 2025.02 R
CDVI Censor Dependent Variational Inference ICML 2025.05 Pytorch
ALD Learning Survival Distributions with the Asymmetric Laplace Distribution ICML 2025.05 Pytorch

Objective Functions

Keyword Title Publisher Date Code Notes
GBMCI A Gradient Boosting Algorithm for Survival Analysis via Direct Optimazation of Concordance Index Computational and Mathematical Methods in Medicine 2013.09 R
Survival-CRPS Countdown Regression: Sharp and Calibrated Survival Predictions UAI 2019 PyTorch
Bias in Cross-Entropy-Based Training of Deep Survival Networks TPAMI 2020.03
SFM Calibration and Uncertainty in Neural Time-to-Event Modeling TNNLS 2020.09 TensorFlow
X-CAL X-CAL: Explicit Calibration for Survival Analysis NeurIPS 2020 PyTorch Poster
Discrete-RPS Estimating Calibrated Individualized Survival Curves with Deep Learning AAAI 2021.02 PyTorch
KL-Calibration Simpler Calibration for Survival Analysis ICLR OpenReview 2021.10
SuMo-net Survival regression with proper scoring rules and monotonic neural networks AIStats 2022.03 PyTorch
DQS Proper Scoring Rules for Survival Analysis ICML 2023.06 PyTorch Poster

Time-varying Covariates Models

Keyword Title Publisher Date Code Notes
SPH Survival Prediction by an Integrated Learning Criterion on Intermittently Varying Healthcare Data AAAI 2016.02
Time-varying Cox Time-varying covariates and coefficients in Cox regression models Annals of Translational Medicine 2018.01
DRSA Deep Recurrent Survival Analysis AAAI 2019.02 TensorFlow
TSNN Time-Dependent Survival Neural Network for Remaining Useful Life Prediction PAKDD 2019.03
Dynamic-DeepHit Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data TBME 2019.04 TensorFlow
TSNN & RSNN Survival neural networks for time-to-event prediction in longitudinal study Knowledge and Information System 2020.05 Extend Paper
DRSM Deep Parametric Time-to-Event Regression with Time-Varying Covariates AAAI Spring Symposium (SP-ACA) 2021.03 PyTorch
SubLign Clustering Interval-Censored Time-Series for Disease Phenotyping AAAI 2022.02
TCSA Temporally-Consistent Survival Analysis NeurIPS 2022.11 Python Poster
SurvPP Survival Permanental Processes for Survival Analysis with Time-Varying Covariates NeurIPS 2023.12 Python
CoxSig Dynamic Survival Analysis with Controlled Latent States ICML 2024.01 PyTorch
DSPS Support vector machine for dynamic survival prediction with time-dependent covariates Ann. Appl. Stat. 2024.09 R

Explainable Survival Models

Keyword Title Publisher Date Code Notes
SPIE Simultaneous Prediction Intervals for Patient-Specific Survival Curves IJCAI 2019 Python
SurvLIME SurvLIME: A method for explaining machine learning survival models Knowledge-Based Systems 2020.09 Python
AutoScore-Survival AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data Journal of Biomedical Informatics 2022.01 R
EXCEL Explainable Censored Learning: Finding Critical Features with Long Term Prognostic Values for Survival Prediction Arxiv 2022.09
BNN-ISD Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction IEEE TBME 2023.07 PyTorch

Competing Risks and Multi-Event Models

Keyword Title Publisher Date Code Notes
On pseudo-values for regression analysis in competing risks models Lifetime Data Analysis 2009.06
The Survival Filter: Joint Survival Analysis with a Latent Time Series UAI 2015
DMGP Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks NeurIPS 2017.12
DeepHit DeepHit: A Deep Learning Approach to Survival Analysis with Competing Risks AAAI 2018.02 TensorFlow
DSM Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data With Competing Risks IEEE JBHI 2021.01 PyTorch
HSA A Hierarchical Approach to Multi-Event Survival Analysis AAAI 2021.05 PyTorch
SurvTRACE SurvTRACE: Transformers for Survival Analysis with Competing Events Arxiv 2021.10 Pytorch
Deep-CSA Deep-CSA: Deep Contrastive Learning for Dynamic Survival Analysis with Competing Risks IEEE JBHI 2022.04
DeepPseudo DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis KDD DSHealth Workshop 2022.08
SurvivalBoost Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks AIStats 2025.02

Generalized Survival Analysis Methods

Title Publisher Date Code Notes
Pseudo-observations Pseudo-observations in survival analysis Statistical Methods in Medical Research 2010
A doubly robust censoring unbiased transformation The International Journal of Biostatistics 2007.03
Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting Journal of Biomedical Informatics 2016.03 R
A General Machine Learning Framework for Survival Analysis ECML 2020.06 R
Parametrics Pseudo-observations Regression models using parametric pseudo-observations Statistics in Medicine 2020.06
A Kernel Log-Rank Test of Independence for Right-Censored Data JASA 2021.09 Python
CSA Conformalized survival analysis JRSS: Series B 2023.01 R
anchor-vis A General Framework for Visualizing Embedding Spaces of Neural Survival Analysis Models Based on Angular Information CHIL 2023.07 Python
Adaptive-CSA Conformalized survival analysis with adaptive cut-offs Biometrika 2023.12 R
CSD Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration ICML 2024.05 Python Poster
CiPOT Toward Conditional Distribution Calibration in Survival Prediction NeurIPS 2024.10 Python Poster
Fused Conformalized Survival Analysis for General Right-Censored Data ICLR 2025.02

Evaluation Metrics

Keyword Title Publisher Date Code Notes
Brier Score Decomposition The Comparison and Evaluation of Forecasters The Statistician 1983
CRPS Decomposition Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems Weather and Forecasting 2000.03
IPCW Brier Score Assessment and Comparison of Prognostic Classification Schemes for Survival Data Statistics in Medicine 1999.09
Administrative Brier Score The Brier Score under Administrative Censoring: Problems and Solutions JMLR 2019.12 PyTorch PyCox 3-3
Graphical-Cal Graphical calibration curves and the integrated calibration index (ICI) for survival models Statistics in Medicine 2019.11 Python
D-Calibration Effective Ways to Build and Evaluate Individual Survival Distributions JMLR 2020.06 R
KSD Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data ICML 2020.08
Scoring rules in survival analysis Arxiv 2022.12
MAE-PO An Effective Meaningful Way to Evaluate Survival Models ICML 2023.06 PyTorch Poster

Causal Inference

Keyword Title Publisher Date Code Notes
Causal inference in survival analysis using pseudo-observations Statistics in Medicine 2017.03
CausalTree Causal Inference for Survival Analysis Arvix 2018.03 R
CSA Enabling Counterfactual Survival Analysis with Balanced Representations ACM CHIL 2021.03 Python
SurvITE SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data NeurIPS 2021.10 TensorFlow
CMHE Counterfactual Phenotyping with Censored Time-to-Events KDD 2022.02 PyTorch
DNMC Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data AISTATS 2022.03 TensorFlow
compCATE Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data AISTATS 2023.02 Python
PCI2S Regression-based proximal causal inference for right-censored time-to-event data Arxiv 2024.09 R
Doubly protected estimation for survival outcomes utilizing external controls for randomized clinical trials ICML 2025.05 R?

Fairness

Keyword Title Publisher Date Code Notes
FSRF Longitudinal Fairness with Censorship AAAI 2022.03
FISA Fair and Interpretable Models for Survival Analysis KDD 2022.08 Video
IFS Censored Fairness through Awareness AAAI 2023.03
Fairness-Aware Processing Techniques in Survival Analysis: Promoting Equitable Predictions ECML-PKDD 2023.09
DRO-Cox Fairness in Survival Analysis with Distributionally Robust Optimization JMLR 2024.08 PyTorch
FairFSA Fair Federated Survival Analysis AAAI 2025.04

Out-Of-Distribution

Keyword Title Publisher Date Code Notes
Evaluating Domain Generalization for Survival Analysis in Clinical Studies CHIL 2022.08
Stable-Cox Stable Cox regression for survival analysis under distribution shifts Nature Machine Intelligence 2024.12 PyTorch

Dependent Censoring and Competing Risks

Keyword Title Publisher Date Code Notes
Copula Based Cox Proportional Hazards Models for Dependent Censoring JASA 2023.03 R
CopulaDeepSurvival Copula-Based Deep Survival Models for Dependent Censoring UAI 2023.06 PyTorch
DCSurvival Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees AAAI 2023.12 PyTorch
PSA Proximal survival analysis to handle dependent right censoring JRSS: Series B 2024.05
HACSurv HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks AIStats 2025.02 PyTorch
SC-Net Survival Analysis via Density Estimation ICML 2025.02 PyTorch

Synthetic Data Generation

Keyword Title Publisher Date Code Notes
SurvivalGAN SurvivalGAN: Generating Time-to-Event Data for Survival Analysis AIStats 2023.02 PyTorch
SYNDSURV: A simple framework for survival analysis with data distributed across multiple institutions Computers in Biology and Medicine 2024.04 PyTorch
Conditioning on Time is All You Need for Synthetic Survival Data Generation Arxiv 2024.05 PyTorch

Temporal Time Process

Title Publisher Date Code Notes
Lecture Notes: Temporal Point Processes and the Conditional Intensity Function Arxiv 2018.06
Temporal Point Processes Course Material 2019.01
Recent Advance in Temporal Point Process: from Machine Learning Perspective 2019
Wavelet Reconstruction Networks for Marked Point Processes AAAI Spring Symposium (SP-ACA) 2021.03 Python
Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations ICLR 2024.01

Applied Survival Analysis

Title Publisher Date Code Notes
Empirical comparisons between Kaplan-Meier and Nelson-Aalen survival function estimators Journal of Statistical Computation and Simulation 2002
Machine-Learning Approaches in COVID-19 Survival Analysis and Discharge-Time Likelihood Prediction Using Clinical Data Patterns 2020.08 Python
Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database Lancet Digital Health 2021.03 Python
Learning accurate personalized survival models for predicting hospital discharge and mortality of COVID-19 patients Scientific Report 2022.03 R
Predicting Time-to-conversion for Dementia of Alzheimer's Type using Multi-modal Deep Survival Analysis Arxiv 2022.05
Time-to-event modeling for hospital length of stay prediction for COVID-19 patients Machine Learning with Applications 2022.09
Metabolomic profiles predict individual multidisease outcomes Nature Medicine 2022.09 PyTorch
Personalized breast cancer onset prediction from lifestyle and health history information PLOS One 2022.12
SurProGenes: Survival Risk-Ordered Representation of Cancer Patients and Genes for the Identification of Prognostic Genes ICML 2023.06 TensorFLow Poster
Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model ICML 2023.06 R Poster
Contrastive Learning of Temporal Distinctiveness for Survival Analysis in Electronic Health Records CIKM 2023.10 Python
Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction ICLR 2024.01 PyTorch
MOTOR: A Time-to-Event Foundation Model For Structured Medical Records ICLR 2024.01 PyTorch
Multimodal Prototyping for cancer survival prediction ICML 2024.05 PyTorch
Predicting Long-Term Allograft Survival in Liver Transplant Recipients ML4HC 2024.08 PyTorch
Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images NeurIPS 2024.12 PyTorch Poster
Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology ICLR 2025.02 PyTorch
VAE-Surv: A novel approach for genetic-based clustering and prognosis prediction in myelodysplastic syndromes Computer Methods and Programs in Biomedicine 2025.03 PyTorch
From Representation Space to Prognostic Insights: Whole Slide Image Generation with Hierarchical Diffusion Model for Survival Prediction AAAI 2025.04

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