Neurosurgeons receive extensive technical training, which equips them with the knowledge
and skills to specialise in various fields and manage the massive amounts of information …

This report presents an overview of how machine learning is rapidly advancing clinical
translational imaging in ways that will aid in the early detection, prediction, and treatment of …

Accurate radiogenomic classification of brain tumors is important to improve the standard of
diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we …

Background The peritumoral region (PTR) of glioblastoma (GBM) appears as a T2W-
hyperintensity and is composed of microscopic tumor and edema. Infiltrative low grade …

Recent advances in medical image analysis have been made to improve our understanding
of how disease develops, behaves, and responds to treatment. Magnetic resonance imaging …

Objective The aim of this study was the evaluation radiomics analysis efficacy performed
using computed tomography (CT) and magnetic resonance imaging in the prediction of …

Simple Summary Pancreatic cancer (PC) is one of the deadliest cancers. Its high mortality
rate is correlated with several explanations; the main one is the late disease stage at which …

The current era of advanced computing has allowed for the development and
implementation of the field of radiomics. In pediatric neuro-oncology, radiomics has been …

Simple Summary This study aimed to develop and validate a radiomic model for predicting
overall survival (OS) in glioblastoma multiforme (GBM) patients using pre-treatment MRI …

Based on artificial intelligence (AI), computer-assisted medical diagnosis can scientifically
and efficiently deal with a large quantity of medical imaging data. AI technologies including …