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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 221230 of 472 papers

TitleStatusHype
Predicting Survival Time of Ball Bearings in the Presence of CensoringCode0
Contrastive Learning of Temporal Distinctiveness for Survival Analysis in Electronic Health Records0
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 Genomics0
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 networks0
Towards Flexible Time-to-event Modeling: Optimizing Neural Networks via Rank RegressionCode0
Interpretable ML for High-Frequency Execution0
Exploring novel prognostic biomarkers and biologic processes involved in NASH, cirrhosis and HCC based on survival analysis using systems biology approach0
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