Machine learning and digital health sensing data have led to numerous research
achievements aimed at improving digital health technology. However, using machine …

Lower-grade gliomas (LGG) can eventually progress to glioblastoma (GBM) and death. In
the context of the transfer learning approach, we aimed to train and test an MRI-based …

Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have
increasingly been used to define the best approaches for survival assessment and …

This article introduces a framework for predicting the survival of brain tumor patients by
analyzing magnetic resonance images. The prediction of brain tumor survival is challenging …

Abstract O-6-methylguanine-DNA methyltransferase (MGMT) is one of the most salient gene
promoters that correlates with the effectiveness of standard therapy for patients suffering …

Histopathological whole slide images (WSIs) are the gold standard for cancer diagnosis. In
prognosis, WSIs can also help predict the overall survival (OS) time of cancer (such as …

Imaging is central to the clinical surveillance of brain tumors yet it provides limited insight
into a tumor's underlying biology. Machine learning and other mathematical modeling …

Background The prognosis of advanced gastric cancer (AGC) patients has attracted much
attention, but there is a lack of evaluation method. MRI‐based radiomics has the potential to …

Simple Summary The prognostic expectancies of patients affected by glioblastoma have
remained almost unchanged during the last thirty years. Along with specific oncological …

Glioblastoma Multiforme (GBM), classified as a grade IV glioma by the World Health
Organization (WHO), is a prevalent and notably aggressive form of brain tumor derived from …