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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 211–220 of 472 papers

TitleStatusHype
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
Interpretable machine learning for time-to-event prediction in medicine and healthcareCode1
Continuous Risk Measures for Driving Support—0
Intersection Warning System for Occlusion Risks using Relational Local Dynamic Maps—0
Optimization of Velocity Ramps with Survival Analysis for Intersection Merge-Ins—0
Probabilistic Uncertainty-Aware Risk Spot Detector for Naturalistic Driving—0
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and CountingCode1
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