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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 201–250 of 472 papers

TitleStatusHype
Robust Survival Analysis with Adversarial Regularization—0
SAVAE: Leveraging the variational Bayes autoencoder for survival analysisCode0
MixEHR-SurG: a joint proportional hazard and guided topic model for inferring mortality-associated topics from electronic health recordsCode0
ICTSurF: Implicit Continuous-Time Survival Functions with Neural NetworksCode0
Composite Survival Analysis: Learning with Auxiliary Aggregated Baselines and Survival Scores—0
Cancer Subtype Identification through Integrating Inter and Intra Dataset Relationships in Multi-Omics DataCode0
Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic informationCode0
SurvTimeSurvival: Survival Analysis On The Patient With Multiple Visits/RecordsCode0
Clinical Characteristics and Laboratory Biomarkers in ICU-admitted Septic Patients with and without Bacteremia—0
Likelihood Ratio Confidence Sets for Sequential Decision Making—0
Maximum Likelihood Estimation of Flexible Survival Densities with Importance Sampling—0
Higher Mediterranean diet score is associated with longer time between relapses in Australian females with multiple sclerosis—0
DySurv: dynamic deep learning model for survival analysis with conditional variational inference—0
Improving Event Time Prediction by Learning to Partition the Event Time Space—0
Interpretable Survival Analysis for Heart Failure Risk Prediction—0
A Study on Survival Analysis Methods Using Neural Network to Prevent CancersCode0
Can-SAVE: Mass Cancer Risk Prediction via Survival Analysis Variables and EHR—0
A survey of Transformer applications for histopathological image analysis: New developments and future directionsCode0
Predicting environment effects on breast cancer by implementing machine learning—0
NSOTree: Neural Survival Oblique TreeCode0
Predicting Survival Time of Ball Bearings in the Presence of CensoringCode0
Contrastive Learning of Temporal Distinctiveness for Survival Analysis in Electronic Health Records—0
Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing RisksCode0
Scaling Survival Analysis in Healthcare with Federated Survival Forests: A Comparative Study on Heart Failure and Breast Cancer Genomics—0
Reinterpreting survival analysis in the universal approximator ageCode0
A Deep Learning Approach for Overall Survival Prediction in Lung Cancer with Missing ValuesCode0
Modeling 3D cardiac contraction and relaxation with point cloud deformation networks—0
Towards Flexible Time-to-event Modeling: Optimizing Neural Networks via Rank RegressionCode0
Interpretable ML for High-Frequency Execution—0
Exploring novel prognostic biomarkers and biologic processes involved in NASH, cirrhosis and HCC based on survival analysis using systems biology approach—0
Deep Learning for Cancer Prognosis Prediction Using Portrait Photos by StyleGAN Embedding—0
Cross-Validation Is All You Need: A Statistical Approach To Label Noise EstimationCode0
Structured Learning in Time-dependent Cox ModelsCode0
Copula-Based Deep Survival Models for Dependent Censoring—0
Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort—0
Transformer-based Time-to-Event Prediction for Chronic Kidney Disease DeteriorationCode0
Deep Attentive Survival Analysis in Limit Order Books: Estimating Fill Probabilities with Convolutional-Transformers—0
Learning Survival Distribution with Implicit Survival FunctionCode0
survAIval: Survival Analysis with the Eyes of AI—0
Neural Fine-Gray: Monotonic neural networks for competing risksCode0
A General Framework for Visualizing Embedding Spaces of Neural Survival Analysis Models Based on Angular InformationCode0
Proper Scoring Rules for Survival AnalysisCode0
Diffsurv: Differentiable sorting for censored time-to-event dataCode0
Interpretable (not just posthoc-explainable) heterogeneous survivor bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions—0
Using Geographic Location-based Public Health Features in Survival AnalysisCode0
Searching for the "Holy Grail" of sponsorship-linked marketing: A generalizable sponsorship ROI model—0
Une comparaison des algorithmes d'apprentissage pour la survie avec données manquantes—0
CLSA: Contrastive Learning-based Survival Analysis for Popularity Prediction in MEC Networks—0
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study—0
Continuous Risk Measures for Driving Support—0
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