Background Magnetic resonance imaging (MRI) and amino acid positron-emission
tomography (PET) of the brain contain a vast amount of structural and functional information …

This review delves into the most recent advancements in applying artificial intelligence (AI)
within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors …

Glioblastoma (GBM) is the most aggressive and invasive primary brain tumor. Current
therapies are not curative, and patients' outcomes remain poor with an overall survival of …

Glioblastoma (GBM) is the most common malignant tumor of the central nervous system with
poor prognosis. Although the field of immunotherapy in glioma is developing rapidly …

As a highly malignant tumor, the incidence and mortality of glioma are not optimistic.
Predicting the survival time of patients with glioma by extracting the feature information from …

Objective Monitoring biomarkers using machine learning (ML) may determine glioblastoma
treatment response. We systematically reviewed quality and performance accuracy of …

Objective To develop a radiomics risk score based on dynamic contrast-enhanced (DCE)
MRI for prognosis prediction in patients with glioblastoma. Materials and Methods One …

Glioblastoma remains the most devastating brain tumor despite optimal treatment, because
of the high rate of recurrence. Distant recurrence has distinct genomic alterations compared …

Adult-type diffuse glioma (grade 4) has infiltrating nature, and therefore local progression is
likely to occur within surrounding non-enhancing T2 hyperintense areas even after gross …

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival
of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate …