AIMC Topic: Glioma
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Systematic review and epistemic meta-analysis to advance binomial AI-radiomics integration for predicting high-grade glioma progression and enhancing patient management.
Scientific reports
May 8, 2025
High-grade gliomas, particularly glioblastoma (MeSH:Glioblastoma), are among the most aggressive and lethal central nervous system tumors, necessitating advanced diagnostic and prognostic strategies. This systematic review and epistemic meta-analysis...
Unsupervised Deep Learning for Blood-Brain Barrier Leakage Detection in Diffuse Glioma Using Dynamic Contrast-enhanced MRI.
Radiology. Artificial intelligence
May 1, 2025
Purpose To develop an unsupervised deep learning framework for generalizable blood-brain barrier leakage detection using dynamic contrast-enhanced MRI, without requiring pharmacokinetic models and arterial input function estimation. Materials and Met...
Improving Deep Learning Models for Pediatric Low-Grade Glioma Tumours Molecular Subtype Identification Using MRI-based 3D Probability Distributions of Tumour Location.
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
May 1, 2025
Pediatric low-grade gliomas (pLGG) are the most common brain tumour in children, and the molecular diagnosis of pLGG enables targeted treatment. We use MRI-based Convolutional Neural Networks (CNNs) for molecular subtype identification of pLGG and a...
An Attention-Based Deep Neural Network Model to Detect Cis-Regulatory Elements at the Single-Cell Level From Multi-Omics Data.
Genes to cells : devoted to molecular & cellular mechanisms
Mar 1, 2025
Cis-regulatory elements (cREs) play a crucial role in regulating gene expression and determining cell differentiation and state transitions. To capture the heterogeneous transitions of cell states associated with these processes, detecting cRE activi...
Multimodal deep learning improves recurrence risk prediction in pediatric low-grade gliomas.
Neuro-oncology
Jan 12, 2025
BACKGROUND: Postoperative recurrence risk for pediatric low-grade gliomas (pLGGs) is challenging to predict by conventional clinical, radiographic, and genomic factors. We investigated if deep learning (DL) of magnetic resonance imaging (MRI) tumor f...
Brain tumor classification using MRI images and deep learning techniques.
PloS one
Jan 1, 2025
Brain tumors pose a significant medical challenge, necessitating early detection and precise classification for effective treatment. This study aims to address this challenge by introducing an automated brain tumor classification system that utilizes...
Integrative Machine Learning of Glioma and Coronary Artery Disease Reveals Key Tumour Immunological Links.
Journal of cellular and molecular medicine
Jan 1, 2025
It is critical to appreciate the role of the tumour-associated microenvironment (TME) in developing strategies for the effective therapy of cancer, as it is an important factor that determines the evolution and treatment response of tumours. This wor...
Deciphering the Role of SLFN12: A Novel Biomarker for Predicting Immunotherapy Outcomes in Glioma Patients Through Artificial Intelligence.
Journal of cellular and molecular medicine
Dec 1, 2024
Gliomas are the most prevalent form of primary brain tumours. Recently, targeting the PD-1 pathway with immunotherapies has shown promise as a novel glioma treatment. However, not all patients experience long-lasting benefits, underscoring the necess...
Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma.
Neuro-oncology
Nov 4, 2024
BACKGROUND: Formalin-fixed, paraffin-embedded (FFPE) tissue slides are routinely used in cancer diagnosis, clinical decision-making, and stored in biobanks, but their utilization in Raman spectroscopy-based studies has been limited due to the backgro...
Diffusion-weighted MRI precisely predicts telomerase reverse transcriptase promoter mutation status in World Health Organization grade IV gliomas using a residual convolutional neural network.
The British journal of radiology
Nov 1, 2024
OBJECTIVES: Telomerase reverse transcriptase promoter (pTERT) mutation status plays a key role in making decisions and predicting prognoses for patients with World Health Organization (WHO) grade IV glioma. This study was conducted to assess the valu...
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