mlsanityData to 7 Oct 2026

Deep Survival Analysis

arXiv 1608.02158 ↗First posted 6 Aug 2016stat.ML cs.AI stat.MEcited by 60

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Abstract (arXiv)

The electronic health record (EHR) provides an unprecedented opportunity to build actionable tools to support physicians at the point of care. In this paper, we investigate survival analysis in the context of EHR data. We introduce deep survival analysis, a hierarchical generative approach to survival analysis. It departs from previous approaches in two primary ways: (1) all observations, including covariates, are modeled jointly conditioned on a rich latent structure; and (2) the observations are aligned by their failure time, rather than by an arbitrary time zero as in traditional survival analysis. Further, it (3) scalably handles heterogeneous (continuous and discrete) data types that occur in the EHR. We validate deep survival analysis model by stratifying patients according to risk of developing coronary heart disease (CHD). Specifically, we study a dataset of 313,000 patients corresponding to 5.5 million months of observations. When compared to the clinically validated Framingham CHD risk score, deep survival analysis is significantly superior in stratifying patients according to their risk.

Key facts. Cited by 60 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Aug 2016.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 15; 2022: 11; 2023: 13; 2024: 5; 2025: 12; 2026: 4.

60 papers.

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  1. 2023Deep Learning for Survival Analysis: A Reviewcited by 75
  2. 2021Deep Cox Mixtures for Survival Regressioncited by 43
  3. 2021Survival Regression with Proper Scoring Rules and Monotonic Neural Networkscited by 42
  4. 2021SurvTRACE: Transformers for Survival Analysis with Competing Eventscited by 40
  5. 2021X-CAL: Explicit Calibration for Survival Analysiscited by 30
  6. 2021Towards Generating Real-World Time Series Datacited by 26
  7. 2021A Deep Variational Approach to Clustering Survival Datacited by 25
  8. 2021SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Datacited by 25
  9. 2022auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Datacited by 17
  10. 2023SurvivalGAN: Generating Time-to-Event Data for Survival Analysiscited by 17
  11. 2021SurvNAM: The machine learning survival model explanationcited by 16
  12. 2022Counterfactual Phenotyping with Censored Time-to-Eventscited by 13
38 more
  1. 2022SurvLatent ODE : A Neural ODE based time-to-event model with competing risks for longitudinal data improves cancer-associated Venous Thromboembolism (VTE) predictioncited by 13
  2. 2022DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysiscited by 12
  3. 2022Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guaranteecited by 9
  4. 2022Survival Mixture Density Networkscited by 9
  5. 2021Inverse-Weighted Survival Gamescited by 8
  6. 2022The Concordance Index decomposition: A measure for a deeper understanding of survival prediction modelscited by 8
  7. 2023Contrastive Learning of Temporal Distinctiveness for Survival Analysis in Electronic Health Recordscited by 5
  8. 2021Individual Survival Curves with Conditional Normalizing Flowscited by 4
  9. 2022A State Transition Model for Mobile Notifications via Survival Analysiscited by 4
  10. 2023SAVAE: Leveraging the variational Bayes autoencoder for survival analysiscited by 4
  11. 2021Leveraging Deep Representations of Radiology Reports in Survival Analysis for Predicting Heart Failure Patient Mortalitycited by 3
  12. 2022Deep conditional transformation models for survival analysiscited by 3
  13. 2023Deep Clustering Survival Machines with Interpretable Expert Distributionscited by 3
  14. 2023Explainable Predictive Maintenancecited by 3
  15. 2024Generating Survival Interpretable Trajectories and Datacited by 3
  16. 2026SVL: Goal-Conditioned Reinforcement Learning as Survival Learningcited by 3
  17. 2023A General Framework for Visualizing Embedding Spaces of Neural Survival Analysis Models Based on Angular Informationcited by 2
  18. 2024Generating Accurate Synthetic Survival Data by Conditioning on Outcomescited by 2
  19. 2024Deep State-Space Generative Model For Correlated Time-to-Event Predictionscited by 2
  20. 2025SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysiscited by 2
  21. 2021Variational Bayes survival analysis for unemployment modellingcited by 1
  22. 2021Boost-R: Gradient Boosted Trees for Recurrence Datacited by 1
  23. 2022BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effectcited by 1
  24. 2023Learning Survival Distribution with Implicit Survival Functioncited by 1
  25. 2023NSOTree: Neural Survival Oblique Treecited by 1
  26. 2023Maximum Likelihood Estimation of Flexible Survival Densities with Importance Samplingcited by 1
  27. 2023MixEHR-SurG: a joint proportional hazard and guided topic model for inferring mortality-associated topics from electronic health recordscited by 1
  28. 2024Confidence Intervals and Simultaneous Confidence Bands Based on Deep Learningcited by 1
  29. 2025Censor Dependent Variational Inferencecited by 1
  30. 2025FinSurvival: A Suite of Large Scale Survival Modeling Tasks from Financecited by 1
  31. 2025Dynamic Survival Prediction using Longitudinal Images based on Transformercited by 1
  32. 2025SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysiscited by 1
  33. 2025Let the Experts Speak: Improving Survival Prediction & Calibration via Mixture-of-Experts Headscited by 1
  34. 2025SurvBench: A Standardised Preprocessing Pipeline for Multi-Modal Electronic Health Record Survival Analysiscited by 1
  35. 2026Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networkscited by 1
  36. 2026Computational Identifiabilitycited by 1
  37. 2021Risk markers by sex for in-hospital mortality in patients with acute coronary syndrome: a machine learning approachcited by 0
  38. 2021Metaparametric Neural Networks for Survival Analysiscited by 0

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