Besides the broad development of nanotechnological approaches for cancer diagnosis and
therapy, currently, there is no significant progress in the treatment of different types of brain …

Deep learning has remarkably impacted several different scientific disciplines over the last
few years. For example, in image processing and analysis, deep learning algorithms were …

Brain tumor diagnosis and classification still rely on histopathological analysis of biopsy
specimens today. The current method is invasive, time-consuming and prone to manual …

The study of neuroimaging is a very important tool in the diagnosis of central nervous system
tumors. This paper presents the evaluation of seven deep convolutional neural network …

Cancer is a major medical problem worldwide. Due to its high heterogeneity, the use of the
same drugs or surgical methods in patients with the same tumor may have different curative …

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 …

Cancer is associated with significant morbimortality globally. Advances in screening,
diagnosis, management and survivorship were substantial in the last decades, however …

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

Simple Summary With the advancement of artificial intelligence, including machine learning,
the field of oncology has seen promising results in cancer detection and classification …

Treatment of glioblastoma xenografts with chloroquine results in macroautophagy/
autophagy inhibition, resulting in a reduction of tumor hypoxia and sensitization to radiation …