Survival Prediction Across Diverse Cancer Types Using Neural Networks

arXiv:2404.08713v1 Announce Type: cross
Abstract: Gastric cancer and Colon adenocarcinoma represent widespread and challenging malignancies with high mortality rates and complex treatment landscapes. In response to the critical need for accurate prognosis in cancer patients, the medical community has embraced the 5-year survival rate as a vital metric for estimating patient outcomes. This study introduces a pioneering approach to enhance survival prediction models for gastric and Colon adenocarcinoma patients. Leveraging advanced image analysis techniques, we sliced whole slide images (WSI) …

abstract arxiv cancer community cs.lg diverse eess.iv medical mortality networks neural networks patient patients prediction q-bio.qm rate survival treatment type types vital