Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

MGMT promoter methylation prediction based on multiparametric MRI via vision graph neural network

16 Feb 2024

Abstract excerpt

PurposeGlioblastoma (GBM) is aggressive and malignant. The methylation status of the O6‐methylguanine‐DNA methyltransferase (MGMT) promoter in GBM tissue is considered an important biomarker for developing the most effective treatment plan. Although the standard method for assessing the MGMT promoter methylation status is via bisulfite modification and deoxyribonucleic acid (DNA) sequencing of biopsy or surgical...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Epigenetics and DNA Methylation
Share to Glioma Diagnosis and Treatment
Share to Radiomics and Machine Learning in Medical Imaging

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 38370421
DOI: 10.1117/1.jmi.11.1.014503

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

MGMT promoter methylation prediction based on multiparametric MRI via vision graph neural networkPMID 38370421Read ↗

Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysisSemantic proximity Read ↗

MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning modelsSemantic proximity Read ↗

Radiogenomic Prediction of MGMT Promoter Methylation Status in Glioblastoma Using Multi-Modal MRI and EfficientNetSemantic proximity Read ↗

A Self-attention Graph Convolutional Network for Precision Multi-tumour Early Diagnostics with DNA Methylation DataSemantic proximity Read ↗

Automated machine learning to predict the co-occurrence of isocitrate dehydrogenase mutations and O6 -methylguanine-DNA methyltransferase promoter methylation in patients with gliomas.Semantic proximity Read ↗

Prediction of IDH and 1p/19q Status in Gliomas Based on Dual Structural Feature Exploration and Alignment Network.Semantic proximity Read ↗

GLIA-Deep: Glioblastoma Image Analysis Using Deep Learning Convolutional Neural Networks to Accurately Classify Gene Methylation and Predict Drug EffectivenessSemantic proximity Read ↗

Radiological model based on the standard magnetic resonance sequences for detecting methylguanine methyltransferase methylation in glioma using texture analysisSemantic proximity Read ↗

Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: A neuro-oncological investigationSemantic proximity Read ↗

Competent Radiogenomics Features for the Prediction of glioma MutationsSemantic proximity Read ↗

A Self-attention Graph Convolutional Network for Precision Multi-tumour Early Diagnostics with DNA Methylation DataSemantic proximity Read ↗

Predicting MGMT Methylation in Glioblastoma for Informed Clinical Decisions: An AI-Driven Approach in Resource-Limited SettingsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.