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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 451–472 of 472 papers

TitleStatusHype
Optimization of Velocity Ramps with Survival Analysis for Intersection Merge-Ins—0
Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data—0
Pathology-genomic fusion via biologically informed cross-modality graph learning for survival analysis—0
Penalized Deep Partially Linear Cox Models with Application to CT Scans of Lung Cancer Patients—0
Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors—0
Playtime Measurement with Survival Analysis—0
Positive-Unlabelled Survival Data Analysis—0
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data—0
Predicting Breast Cancer Survival: A Survival Analysis Approach Using Log Odds and Clinical Variables—0
Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach—0
Predicting Customer Churn in World of Warcraft—0
Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling—0
Predicting environment effects on breast cancer by implementing machine learning—0
Predicting Kidney Transplant Survival using Multiple Feature Representations for HLAs—0
Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort—0
Predicting risk of late age-related macular degeneration using deep learning—0
Predicting Session Length in Media Streaming—0
Predicting Survival Outcomes in the Presence of Unlabeled Data—0
Predicting the Lifespan of Industrial Printheads with Survival Analysis—0
Predicting Time-to-conversion for Dementia of Alzheimer's Type using Multi-modal Deep Survival Analysis—0
Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data—0
Prediction of Delirium Risk in Mild Cognitive Impairment Using Time-Series data, Machine Learning and Comorbidity Patterns -- A Retrospective Study—0
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