Simple Summary Glioblastoma multiforme (GBM) are among the most lethal tumors. The
highly invasive nature and presence of GBM stem cells, as well as the blood brain barrier …

Neuroimaging is critical in clinical care and research, enabling us to investigate the brain in
health and disease. There is a complex link between the brain's morphological structure …

Deep learning (DL) is a breakthrough technology for medical imaging with high sample size
requirements and interpretability issues. Using a pretrained DL model through a radiomics …

Introduction Lymphovascular space invasion (LVSI) is associated with lymph node
metastasis and poor prognosis in cervical cancer. In this study, we investigated the potential …

Objectives The tumor microenvironment and immune cell infiltration (ICI) associated with
glioblastoma (GBM) play a vital role in cancer development, progression, and prognosis …

Given the recent advances in molecular pathogenesis of tumors, with better correlation with
tumor behavior and prognosis, major changes were made to the new 2021 World Health …

Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral
spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to …

Deep learning models have been developed for various predictions in glioma; yet, they were
constrained by manual segmentation, task-specific design, or a lack of biological …

Based on artificial intelligence (AI), computer-assisted medical diagnosis can scientifically
and efficiently deal with a large quantity of medical imaging data. AI technologies including …

Purpose This study aims to assess the diagnostic value of ultrasound habitat sub-region
radiomics feature parameters using a fully connected neural networks (FCNN) combination …