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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

Showing 2650 of 472 papers

TitleStatusHype
Forecasting from Clinical Textual Time Series: Adaptations of the Encoder and Decoder Language Model Families0
Offline Dynamic Inventory and Pricing Strategy: Addressing Censored and Dependent DemandCode0
Predicting the Lifespan of Industrial Printheads with Survival Analysis0
ICBM community cancer registry analysis: a focus on Non-Hodgkin Lymphoma cases in missileers0
Interpretable Non-linear Survival Analysis with Evolutionary Symbolic RegressionCode0
Predicting Survivability of Cancer Patients with Metastatic Patterns Using Explainable AICode1
Vision Transformers with Autoencoders and Explainable AI for Cancer Patient Risk Stratification Using Whole Slide Imaging0
Extending Cox Proportional Hazards Model with Symbolic Non-Linear Log-Risk Functions for Survival AnalysisCode0
Improving Diseases Predictions Utilizing External Bio-Banks0
AdaMHF: Adaptive Multimodal Hierarchical Fusion for Survival PredictionCode0
VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic ReconstructionCode0
Interpretable Deep Regression Models with Interval-Censored Failure Time Data0
A novel gradient-based method for decision trees optimizing arbitrary differential loss functionsCode0
Ensemble Survival Analysis for Preclinical Cognitive Decline Prediction in Alzheimer's Disease Using Longitudinal Biomarkers0
Survival Analysis with Machine Learning for Predicting Li-ion Battery Remaining Useful LifeCode1
Generalized Bayesian Ensemble Survival Tree (GBEST) model0
Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event DataCode0
Attention-Based Synthetic Data Generation for Calibration-Enhanced Survival Analysis: A Case Study for Chronic Kidney Disease Using Electronic Health Records0
Adaptive Prototype Learning for Multimodal Cancer Survival AnalysisCode0
MIRROR: Multi-Modal Pathological Self-Supervised Representation Learning via Modality Alignment and RetentionCode1
Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis0
Overcoming Dependent Censoring in the Evaluation of Survival ModelsCode0
Enhancing External Validity of Experiments with Ongoing Sampling0
Censor Dependent Variational InferenceCode0
4D VQ-GAN: Synthesising Medical Scans at Any Time Point for Personalised Disease Progression Modelling of Idiopathic Pulmonary Fibrosis0
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