The natural history and treatment landscape of primary brain tumours are complicated by the
varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low …

This article is a comprehensive review of the basic background, technique, and clinical
applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A …

Gliomas can be classified into five molecular groups based on the status of IDH mutation,
1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by …

Background Accurate characterization of glioma is crucial for clinical decision making. A
delineation of the tumor is also desirable in the initial decision stages but is time-consuming …

Abstract Purpose of Review This review will explore the latest in advanced imaging
techniques, with a focus on the complementary nature of multiparametric, multimodality …

Definition Predictive modeling is a complex methodology that involves leveraging advanced
mathematical and computational techniques to forecast future occurrences or outcomes …

Machine learning (ML) models have been shown to predict the presence of clinical factors
from medical imaging with remarkable accuracy. However, these complex models can be …

Glioma grading is critical in treatment planning and prognosis. This study aims to address
this issue through MRI-based classification to develop an accurate model for glioma …

Gliomas are a heterogenous group of central nervous system tumors with different outcomes
and different therapeutic needs. Glioblastoma, the most common subtype in adults, has a …

Hundreds of millions of people around the world suffer from neurological disorders or have
experienced them intermittently, which has significantly reduced their quality of life. The …