A General Machine Learning Framework for Survival Analysis

27 Jun 2020Andreas BenderDavid RügamerFabian ScheiplBernd Bischl

The modeling of time-to-event data, also known as survival analysis, requires specialized methods that can deal with censoring and truncation, time-varying features and effects, and that extend to settings with multiple competing events. However, many machine learning methods for survival analysis only consider the standard setting with right-censored data and proportional hazards assumption... (read more)

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