Survival analysis concerns the study of timeline data where the event of interest may remain unobserved (i.e., censored). Studies commonly record more than one type of event, but conventional survival techniques focus on a single event type. We set out to integrate both multiple independently censored time-to-event variables as well as missing observations. An energy-based approach is taken with a bi-partite structure between latent and visible states, known as harmoniums (or restricted Boltzmann machines). The present harmonium is shown, both theoretically and experimentally, to capture non-linearly separable patterns between distinct time recordings. We illustrate on real world data that, for a single time-to-event variable, our model is on par with established methods. In addition, we demonstrate that discriminative predictions improve by leveraging an extra time-to-event variable. In conclusion, multiple time-to-event variables can be successfully captured within the harmonium paradigm.
翻译:生存分析涉及对时间期限数据的研究,其中感兴趣的事件可能仍然得不到观察(即受审查的)。研究通常记录不止一种事件,但常规生存技术侧重于单一事件类型。我们着手将多个独立审查的时间到活动变量和缺失的观测结合起来。在潜在状态和可见状态(称为合声器(或受限制的波尔茨曼机器))之间的双面结构中,采用了基于能源的方法。目前的合声器在理论上和实验上都显示,可以捕捉不同时间记录之间的非线性分离模式。我们用真实世界数据来说明,对于单一的时间到事件变量来说,我们的模式与既定方法完全相同。此外,我们还表明,通过利用额外的时间到活动变量来改进了基于歧视的预测。最后,多种时间到活动变量可以在合音模式中成功捕捉到。</s>