Feb 6, 2017 · In doing so, we aim to solve the problem of Just-In-Time recommendation, that is, to recommend the right items at the right time. We use tools.

We present a model based on Long-Short Term Memory to estimate when a user will return to a site and what their future listening behavior will be. In doing so, ...

Feb 26, 2018 · We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's ...

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Disciplina que intenta estimar la probabilidad de supervivencia de un individuo hasta un tiempo T. ○ En nuestro caso definiremos que un usuario “muere” ...

DeepSurv has an advantage over traditional Cox regression because it does not require an a priori selection of covariates, but learns them adaptively. DeepSurv ...

May 20, 2019 · Bibliographic details on Neural Survival Recommender.

We propose a very different method with two simple steps. In the first step, we transform each subject's survival time into a series of jackknife pseudo ...

Nov 15, 2024 · We propose a diversity reweighted deep survival neural network method with grid optimization (DRGONet) to improve the accuracy of cancer-specific survival risk ...

This study suggests that DeepSurv has the potential to improve the performance of risk prediction models for cardiovascular disease risk factors.