Deep Learning for Survival Analysis: A Review

arXiv:2305.14961v4 Announce Type: replace-cross
Abstract: The influx of deep learning (DL) techniques into the field of survival analysis in recent years has led to substantial methodological progress; for instance, learning from unstructured or high-dimensional data such as images, text or omics data. In this work, we conduct a comprehensive systematic review of DL-based methods for time-to-event analysis, characterizing them according to both survival- and DL-related attributes. In summary, the reviewed methods often address only a small subset of tasks relevant …

analysis arxiv cs.lg deep learning review stat.ml survival type