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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 2130 of 472 papers

TitleStatusHype
MoME: Mixture of Multimodal Experts for Cancer Survival PredictionCode1
Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modelingCode1
A probabilistic estimation of remaining useful life from censored time-to-event dataCode1
Cohort-Individual Cooperative Learning for Multimodal Cancer Survival AnalysisCode1
iMD4GC: Incomplete Multimodal Data Integration to Advance Precise Treatment Response Prediction and Survival Analysis for Gastric CancerCode1
Optimal Survival Trees: A Dynamic Programming ApproachCode1
Tumor Micro-environment Interactions Guided Graph Learning for Survival Analysis of Human Cancers from Whole-slide Pathological ImagesCode1
Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability GuaranteesCode1
HEALNet: Multimodal Fusion for Heterogeneous Biomedical DataCode1
Sensitivity of Survival Analysis MetricsCode1
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