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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 251–275 of 472 papers

TitleStatusHype
TV-SurvCaus: Dynamic Representation Balancing for Causal Survival Analysis—0
Uncovering life-course patterns with causal discovery and survival analysis—0
Une comparaison des algorithmes d'apprentissage pour la survie avec données manquantes—0
Unsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence—0
User Engagement in Mobile Health Applications—0
Using ontology embeddings for structural inductive bias in gene expression data analysis—0
Variable selection for nonlinear Cox regression model via deep learning—0
Variable Selection with Random Survival Forest and Bayesian Additive Regression Tree for Survival Data—0
Variational Bayes survival analysis for unemployment modelling—0
Vision Transformers with Autoencoders and Explainable AI for Cancer Patient Risk Stratification Using Whole Slide Imaging—0
Wavelet feature extraction and genetic algorithm for biomarker detection in colorectal cancer data—0
Weighted Concordance Index Loss-based Multimodal Survival Modeling for Radiation Encephalopathy Assessment in Nasopharyngeal Carcinoma Radiotherapy—0
Comparing ImageNet Pre-training with Digital Pathology Foundation Models for Whole Slide Image-Based Survival Analysis—0
Will Large Language Models Transform Clinical Prediction?—0
WSISA: Making Survival Prediction From Whole Slide Histopathological Images—0
DeepWait: Pedestrian Wait Time Estimation in Mixed Traffic Conditions Using Deep Survival Analysis—0
Delayed Feedback Modeling for the Entire Space Conversion Rate Prediction—0
Development of digitally obtainable 10-year risk scores for depression and anxiety in the general population—0
Differentially Private Regression for Discrete-Time Survival Analysis—0
Discrete Stochastic Models in Continuous Time for Ecology—0
Distributionally Robust Learning in Survival Analysis—0
Dynamic prediction of time to event with survival curves—0
Dynamic Survival Analysis for Early Event Prediction—0
Dynamic Survival Transformers for Causal Inference with Electronic Health Records—0
DySurv: dynamic deep learning model for survival analysis with conditional variational inference—0
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