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Paper abnt 20185/27/2023 However, previous models rely on strong parametric assumptions that are often violated. Much of the previous work has approached the problem by viewing the survival time as the first hitting time of a stochastic process, assuming a specific form for the underlying stochastic process, using available data to learn the relationship between the covariates and the parameters of the model, and then deducing the relationship between covariates and the distribution of first hitting times (the risk). A fundamental problem is to understand the relationship between the covariates and the (distribution of) survival times(times-to-event). Survival analysis (time-to-event analysis) is widely used in economics and finance, engineering, medicine and many other areas. Survival analysis, competing risks, neural networks, first-hitting-time analysis Abstract University of Oxford University of California, Los Angeles Alan Turing Institute
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