Objective (1) To evaluate the diagnostic performance of radiomics in differentiating high-
grade glioma from brain metastasis and how to improve the model.(2) To assess the …

The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-
tailored brain tumor management, achieving optimal onco-functional balance for each …

High-grade gliomas, the most common and aggressive primary brain tumors, are
characterized by a complex tumor microenvironment (TME). Among the immune cells …

Background Recent technological advances have led to the development and
implementation of machine learning (ML) in various disciplines, including neurosurgery. Our …

Simple Summary The pretreatment diagnosis of contrast-enhancing brain tumors is still
challenging in clinical neuro-oncology due to their very similar appearance on conventional …

Brain tumors and brain metastases induce changes in brain tissue remodeling that lead to
immunosuppression and trigger an inflammatory response within the tumor …

BACKGROUND AND PURPOSE: Differentiating glioblastoma from solitary brain metastasis
preoperatively using conventional MR images is challenging. Deep learning models have …

Behçet's syndrome (BS) is a systemic vasculitis with several clinical manifestations.
Neutrophil hyperactivation mediates vascular BS pathogenesis, via both a massive reactive …

Simple Summary We present a systematic review of published reports on machine learning
(ML) applications for the differentiation of gliomas from brain metastases by summarizing …

Simple Summary The process of differentiating glioblastomas from solitary brain metastases
is often difficult using traditional magnetic resonance imaging alone. In the past two …