… of multi-omics data, including genomics data, transcriptomics data and clinical information
in cancer studies, we believe that deep learning would potentially improve cancer prognosis. …

… 3.2 Deep unsupervised representation learning In order to train a pancancer model for
prognosis prediction, we first attempt to compress multiple data modalities into a single feature …

… However, reviews on DL in cancer prognosis prediction models are relatively few. …
prognosis prediction models was systematically reviewed. The following aspects of DL prognostic …

… For pathological tasks for example, we were able to predict the molecular subtype of muscle-…
using deep learning (DL) (9). We also used a similar approach for prognosis prediction in …

… Cancer prognosis and survival Prognosis prediction is an essential part of clinical oncology,
as the expected disease path and likelihood of survival can inform treatment decisions [111]…

… To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep
learning-based models to assist in predicting the diagnosis and overall survival (OS) of GC …

… Multi-omics data are good resources for prognosis and survival prediction; however, these
… novel ensemble framework of deep-learning and machine-learning approaches that robustly …

… An accurate and timely diagnostic and prognostic decision … for cancer diagnosis and prognosis
prediction. In this survey, … for the cancer diagnosis and prognosis prediction tasks. DL is a …

… The most basic cancer prognosis prediction technique relies on population-level estimates
for the specific cancer site and stage. This method fails to take into account the differences …

… In this study, we designed a deep learning framework DCAP to integrate the multi-omics
data for cancer risk estimation. By comparing the prognosis prediction accuracy, the results …