Predicting Survival Outcomes in the Presence of Unlabeled Data. (arXiv:2210.13891v1 [cs.LG])

Many clinical studies require the follow-up of patients over time. This is
challenging: apart from frequently observed drop-out, there are often also
organizational and financial challenges, which can lead to reduced data
collection and, in turn, can complicate subsequent analyses. In contrast, there
is often plenty of baseline data available of patients with similar
characteristics and background information, e.g., from patients that fall
outside the study time window. In this article, we investigate whether we can
benefit from the inclusion …

arxiv data survival