Article

External validation of self-supervised transfer learning for noninvasive molecular subtyping of pediatric low-grade glioma using T2-weighted MRI

2026-01-30

Abstract excerpt

<h4>Purpose</h4> To externally evaluate three binary classification models designed to differentiate the molecular subtype of pediatric low-grade glioma (pLGG) between BRAF Fusion, BRAF Mutation, and Wild Type on T2-weighted magnetic resonance imaging using self-supervised transfer learning, which enables effective performance in a low data setting. <h4>Materials and methods</h4> This retrospective study evaluat...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 8c8ae15c-ed30-5568-b73e-c4980965f1fd
DOI: 10.64898/2026.01.27.26344883

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

External validation of self-supervised transfer learning for noninvasive molecular subtyping of pediatric low-grade glioma using T2-weighted MRIDOI 10.64898/2026.01.27.26344883Read

Noninvasive molecular subtyping of pediatric low-grade glioma with self-supervised transfer learningSemantic proximity Read

Expert-level pediatric brain tumor segmentation in a limited data scenario with stepwise transfer learningSemantic proximity Read

From Voxel to Gene: A Scoping Reviews on MRI Radiogenomics Artificial Intelligence Predictions in Adult Gliomas and Glioblastomas - the Promise of Virtual Biopsy?Semantic proximity Read

Improving the noninvasive classification of glioma genetic subtype with deep learning and diffusion-weighted imaging.Semantic proximity Read

The University of Texas Southwestern Glioma Dataset - MRI, Molecular Markers and Segmentations.Semantic proximity Read

GlioVision: A Multi-Modal MRI Framework for Non-Invasive Glioma Molecular Biomarkers PredictionSemantic proximity Read

Radiomics of Pediatric Low-Grade Gliomas: Toward a Pretherapeutic Differentiation of BRAF-Mutated and BRAF-Fused Tumors.Semantic proximity Read

Unlocking Magnetic Resonance Images Potential: Innovative Brain Tumor Classification via Transfer Learning and Convolutional Neural NetworksSemantic proximity Read

The Performance of Artificial Intelligence in Classifying Molecular Markers in Adult-Type Gliomas Using Histopathological Images: Systematic Review.Semantic proximity Read

Improving radiomics-based isocitrate dehydrogenase 1 prediction in glioma patients using semi-supervised machine learning models.Semantic proximity Read

Deep semi-supervised learning for brain tumor classification.Semantic proximity Read

AI-Powered Segmentation and Prognosis with Missing MRI in Pediatric Brain TumorsSemantic proximity Read