AIMC Topic: Glioma
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A generic support vector machine model for preoperative glioma survival associations.
Radiology
Dec 8, 2014
PURPOSE: To develop a generic support vector machine (SVM) model by using magnetic resonance (MR) imaging-based blood volume distribution data for preoperative glioma survival associations and to prospectively evaluate the diagnostic effectiveness of...
Resting state fMRI feature-based cerebral glioma grading by support vector machine.
International journal of computer assisted radiology and surgery
Sep 17, 2014
PURPOSE : Tumor grading plays an essential role in the optimal selection of solid tumor treatment. Noninvasive methods are needed for clinical grading of tumors. This study aimed to extract parameters of resting state blood oxygenation level-dependen...
Machine Learning-Driven radiomics on 18 F-FDG PET for glioma diagnosis: a systematic review and meta-analysis.
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 26, 2025
BACKGROUND: Machine learning (ML) applied to radiomics has revolutionized neuro-oncological imaging, yet the diagnostic performance of ML models based specifically on ^18F-FDG PET features in glioma remains poorly characterized.
Optimized deep learning for brain tumor detection: a hybrid approach with attention mechanisms and clinical explainability.
Scientific reports
Aug 26, 2025
Brain tumor classification (BTC) from Magnetic Resonance Imaging (MRI) is a critical diagnosis task, which is highly important for treatment planning. In this study, we propose a hybrid deep learning (DL) model that integrates VGG16, an attention mec...
Integrative multi-omics analysis reveals BEST1 as a potential tumor-associated gene in gliomas.
Neuroscience
Aug 6, 2025
BACKGROUND: The newest glioma classification in WHO 2021 emphasizes the importance of gene mutations in the glioma molecular pathogenesis. Our research aims to look for new glioma-related genes that have the potential to be therapeutic targets.
Detection of Brain Cancer Using Genome-wide Cell-free DNA Fragmentomes.
Cancer discovery
Aug 4, 2025
UNLABELLED: Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer diagnosis. In this study, we analyzed genome-wide c...
Predicting p53 Status in IDH-Mutant Gliomas Using MRI-Based Radiomic Model.
Cancer medicine
Aug 1, 2025
OBJECTIVES: Accurate and noninvasive detection of p53 status in isocitrate dehydrogenase mutant (IDH-mt) glioma is clinically meaningful for molecular stratification of glioma, yet it remains challenging. We aimed to investigate the diagnostic effica...
Diagnostic Performance of ChatGPT-4.0 in Histopathological Analysis of Gliomas: A Single Institution Experience.
Neuropathology : official journal of the Japanese Society of Neuropathology
Aug 1, 2025
This study aimed to evaluate the performance of ChatGPT-4.0 as a diagnostic support tool for pathologists in identifying different types of gliomas based on histopathological data and to compare its performance with that of another artificial intelli...
Three-Dimensional Visualisation of Blood Vessels in Human Gliomas Using Tissue Clearing and Deep Learning.
Neuropathology and applied neurobiology
Aug 1, 2025
Gliomas, with their intricate and aggressive nature, call for a detailed visualisation of their vasculature. Traditional 2D imaging often overlooks the spatial heterogeneity of tumours. Our study overcomes this by combining tissue clearing, 3D-confoc...
Applications of artificial intelligence and advanced imaging in pediatric diffuse midline glioma.
Neuro-oncology
Jul 30, 2025
Diffuse midline glioma (DMG) is a rare, aggressive, and fatal tumor that largely occurs in the pediatric population. To improve outcomes, it is important to characterize DMGs, which can be performed via magnetic resonance imaging (MRI) assessment. Re...
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