Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …

Artificial intelligence (AI) continues to transform data analysis in many domains. Progress in
each domain is driven by a growing body of annotated data, increased computational …

Immunotherapy offers the potential for durable clinical benefit but calls into question the
association between tumor size and outcome that currently forms the basis for imaging …

Objectives To develop and validate an efficient and automatically computational approach
for stratifying glioma grades and predicting survival of lower-grade glioma (LGG) patients …

Simple Summary The increasing interest in implementing artificial intelligence in radiomic
models has occurred alongside advancement in the tools used for computer-aided …

Simple Summary As magnetic resonance (MR) intensities are acquired in arbitrary units,
scans from different scanners are not directly comparable; thus, intensity normalization is …

Simple Summary Immune checkpoint inhibitors can be effective drugs to treat cancer.
However, only a minority of patients derive benefits. An important determinant of treatment …

Purpose Recent studies have shown promise of MR-based radiomics in predicting the
survival of patients with untreated glioblastoma. This study aimed to comprehensively collate …

Gliomas are tumors of the central nervous system, which usually start within the glial cells of
the brain or the spinal cord. These are extremely migratory and diffusive tumors, which …

Background and objective Patients with aggressive non-Hodgkin lymphoma (NHL) undergo
distinct therapy strategies compared with indolent NHL patients. However, it is challenging …