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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 51–75 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
Survival Analysis with Machine Learning for Predicting Li-ion Battery Remaining Useful LifeCode1
Adaptive Sampling for Weighted Log-Rank Survival Trees BoostingCode1
SurvLIMEpy: A Python package implementing SurvLIMECode1
Enhancing Uncertainty Quantification in Drug Discovery with Censored Regression LabelsCode1
Tackling Small Sample Survival Analysis via Transfer Learning: A Study of Colorectal Cancer PrognosisCode1
CoxKAN: Kolmogorov-Arnold Networks for Interpretable, High-Performance Survival AnalysisCode1
X-CAL: Explicit Calibration for Survival AnalysisCode1
Hierarchical Bayesian Modelling for Knowledge Transfer Across Engineering Fleets via Multitask LearningCode1
SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation NetworksCode1
CDS -- Causal Inference with Deep Survival Model and Time-varying CovariatesCode1
Cohort-Individual Cooperative Learning for Multimodal Cancer Survival AnalysisCode1
A Closer Look at Mortality Risk Prediction from ElectrocardiogramsCode1
Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability GuaranteesCode1
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction IntervalsCode1
A Wide and Deep Neural Network for Survival Analysis from Anatomical Shape and Tabular Clinical Data—0
A Versatile Influence Function for Data Attribution with Non-Decomposable Loss—0
4D VQ-GAN: Synthesising Medical Scans at Any Time Point for Personalised Disease Progression Modelling of Idiopathic Pulmonary Fibrosis—0
A unified construction for series representations and finite approximations of completely random measures—0
Attention-Based Synthetic Data Generation for Calibration-Enhanced Survival Analysis: A Case Study for Chronic Kidney Disease Using Electronic Health Records—0
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study—0
Continuous Risk Measures for Driving Support—0
Contrastive Learning of Temporal Distinctiveness for Survival Analysis in Electronic Health Records—0
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