Colorectal cancer survival prediction using deep distribution based multiple-instance learning. (arXiv:2204.11294v2 [eess.IV] UPDATED)

Several deep learning algorithms have been developed to predict survival of
cancer patients using whole slide images (WSIs).However, identification of
image phenotypes within the WSIs that are relevant to patient survival and
disease progression is difficult for both clinicians, and deep learning
algorithms. Most deep learning based Multiple Instance Learning (MIL)
algorithms for survival prediction use either top instances (e.g., maxpooling)
or top/bottom instances (e.g., MesoNet) to identify image phenotypes. In this
study, we hypothesize that wholistic information of the …

arxiv cancer distribution prediction survival