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 …

Due to the exponential growth of computational algorithms, artificial intelligence (AI)
methods are poised to improve the precision of diagnostic and therapeutic methods in …

Due to advances in the acquisition and analysis of medical imaging, it is currently possible
to quantify the tumor phenotype. The emerging field of Radiomics addresses this issue by …

Purpose To derive quantitative image features from magnetic resonance (MR) images that
characterize the radiographic phenotype of glioblastoma multiforme (GBM) lesions and to …

Background Radiogenomics is the extension of radiomics through the combination of
genetic and radiomic data. Because genetic testing remains expensive, invasive, and time …

Pseudoprogression (PsP) is a diagnostic clinical dilemma in cancer. In this study, we
retrospectively analyse glioblastoma patients, and using their dynamic susceptibility contrast …

Over the past few decades, the advent and development of genomic assessment methods
and computational approaches have raised the hopes for identifying therapeutic targets that …

In the last few years, biomedical research has been boosted by the technological
development of analytical instrumentation generating a large volume of data. Such …

Purpose: Measurements of objective response rates are critical to evaluate new glioma
therapies. The hallmark metabolic alteration in gliomas with mutant isocitrate …

Background Glioblastoma multiforme (GBM) is the most common and aggressive brain
tumor with poor clinical outcome. Identification and development of new markers could be …