In this paper, we hypothesize that it is possible to localize image regions of preclinical
tumors in a Chest X-ray (CXR) image by a weakly-supervised training of a survival …

Survival time prediction from medical images is important for treatment planning, where
accurate estimations can improve healthcare quality. One issue affecting the training of …

Traditionally, deep learning methods for breast cancer classification perform a single-view
analysis. However, radiologists simultaneously analyze all four views that compose a …

Objectives This study aimed to establish and validate a prognostic model based on
magnetic resonance imaging and clinical features to predict the survival time of patients with …

We presented a novel radiomics approach using multimodality MRI to predict the expression
of an oncogene (O6-Methylguanine-DNA methyltransferase, MGMT) and overall survival …

Glioblastoma (known as glioblastoma multiforme) is one of the most aggressive brain
malignancies, accounting for 48% of all primary brain tumors. For that reason, overall …

Objective Glioblastoma multiforme (GBM), particularly the isocitrate dehydrogenase (IDH)-
wildtype type, represents a significant clinical challenge due to its aggressive nature and …

Predicting brain tumor survival can aid physicians in better assessing the efficacy of
treatments and adjusting treatment plans in clinical practices to enhance patient survival …