mlsanityData to 7 Oct 2026

Deep Neural Networks for Survival Analysis Based on a Multi-Task Framework

arXiv 1801.05512 ↗First posted 17 Jan 2018stat.ML cs.LGcited by 44

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Abstract (arXiv)

Survival analysis/time-to-event models are extremely useful as they can help companies predict when a customer will buy a product, churn or default on a loan, and therefore help them improve their ROI. In this paper, we introduce a new method to calculate survival functions using the Multi-Task Logistic Regression (MTLR) model as its base and a deep learning architecture as its core. Based on the Concordance index (C-index) and Brier score, this method outperforms the MTLR in all the experiments disclosed in this paper as well as the Cox Proportional Hazard (CoxPH) model when nonlinear dependencies are found.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Jan 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 6; 2023: 9; 2024: 11; 2025: 7; 2026: 6.

44 papers.

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  1. 2023Deep Learning for Survival Analysis: A Reviewcited by 75
  2. 2024An Introduction to Deep Survival Analysis Models for Predicting Time-to-Event Outcomescited by 16
  3. 2022An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Datacited by 13
  4. 2024SurvRNC: Learning Ordered Representations for Survival Prediction using Rank-N-Contrastcited by 10
  5. 2024Conformalized Survival Distributions: A Generic Post-Process to Increase Calibrationcited by 10
  6. 2022Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guaranteecited by 9
  7. 2022Survival Mixture Density Networkscited by 9
  8. 2023DySurv: dynamic deep learning model for survival analysis with conditional variational inferencecited by 9
  9. 2021Inverse-Weighted Survival Gamescited by 8
  10. 2021BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo valuescited by 7
  11. 2022Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRIcited by 7
  12. 2023Federated Survival Forestscited by 7
32 more
  1. 2024Evidential time-to-event prediction with calibrated uncertainty quantificationcited by 7
  2. 2023Scaling Survival Analysis in Healthcare with Federated Survival Forests: A Comparative Study on Heart Failure and Breast Cancer Genomicscited by 6
  3. 2023Contrastive Learning of Temporal Distinctiveness for Survival Analysis in Electronic Health Recordscited by 5
  4. 2024Toward Conditional Distribution Calibration in Survival Predictioncited by 5
  5. 2026Tabular Foundation Models Can Do Survival Analysiscited by 5
  6. 2021A Machine Learning Challenge for Prognostic Modelling in Head and Neck Cancer Using Multi-modal Datacited by 3
  7. 2021Lymph Node Graph Neural Networks for Cancer Metastasis Predictioncited by 3
  8. 2022Deep conditional transformation models for survival analysiscited by 3
  9. 2024Advancing Head and Neck Cancer Survival Prediction via Multi-Label Learning and Deep Model Interpretationcited by 3
  10. 2026SVL: Goal-Conditioned Reinforcement Learning as Survival Learningcited by 3
  11. 2023Multimodal Deep Learning for Personalized Renal Cell Carcinoma Prognosis: Integrating CT Imaging and Clinical Datacited by 2
  12. 2025Understanding Overparametrization in Survival Models through Interpolationcited by 2
  13. 2021L1-regularized neural ranking for risk stratification and its application to prediction of time to distant metastasis in luminal node negative chemotherapy na"ive breast cancer patientscited by 1
  14. 2024Advancing Gene Selection in Oncology: A Fusion of Deep Learning and Sparsity for Precision Gene Selectioncited by 1
  15. 2024HuLP: Human-in-the-Loop for Prognosiscited by 1
  16. 2025Let the Experts Speak: Improving Survival Prediction & Calibration via Mixture-of-Experts Headscited by 1
  17. 2022DeepCENT: Prediction of Censored Event Time via Deep Learningcited by 0
  18. 2023Towards Tumour Graph Learning for Survival Prediction in Head & Neck Cancer Patientscited by 0
  19. 2023Diagnosis and Prognosis of Head and Neck Cancer Patients using Artificial Intelligencecited by 0
  20. 2023A personalized Uncertainty Quantification framework for patient survival models: estimating individual uncertainty of patients with metastatic brain tumors in the absence of ground truthcited by 0
  21. 2024Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Informationcited by 0
  22. 2024SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Networkcited by 0
  23. 2024SurvAttack: Black-Box Attack On Survival Models through Ontology-Informed EHR Perturbationcited by 0
  24. 2025Spectral Survival Analysiscited by 0
  25. 2025UNICON: UNIfied CONtinual Learning for Medical Foundational Modelscited by 0
  26. 2025DuPLUS: Dual-Prompt Vision-Language Framework for Universal Medical Image Segmentation and Prognosiscited by 0
  27. 2025MAFM^3: Modular Adaptation of Foundation Models for Multi-Modal Medical AIcited by 0
  28. 2025TraCeR: Transformer-Based Competing Risk Analysis with Longitudinal Covariatescited by 0
  29. 2026Discovering Subgroups with Exceptional Survival Characteristicscited by 0
  30. 2026Investigating Trustworthiness of Nonparametric Deep Survival Models for Alzheimer's Disease Progression Analysiscited by 0
  31. 2026A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadraturecited by 0
  32. 2026Paired Recipient-based Evaluation of Survival Prediction for Deceased Donor Kidney Transplantscited by 0