miscellaneous-9
Survival Analysis
3260 papers • 126 benchmarks • 313 datasets
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.
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Deep Cox Mixtures for Survival Regression
K. Heller, Steve Yadlowsky, Negar Rostamzadeh, Chirag Nagpal•Fri Jan 15 2021
This work describes a new approach for survival analysis regression models, based on learning mixtures of Cox regressions to model individual survival distributions, and proposes an approximation to the Expectation Maximization algorithm for this model that does hard assignments to mixture groups to make optimization efficient.
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