Multiclass machine learning models for molecular subtype identification of pediatric low-grade glioma using bi-institutional MRIs for precision medicine
3 weeks 5 days ago
Pediatric Low-Grade Glioma (pLGG) is the most common pediatric brain tumor, and radiomics-based machine learning (ML) models have shown promise in identifying BRAF fusion and BRAF p.V600E mutation. This bicentric retrospective study included 495 children diagnosed between 1999 and 2023. The local hospital dataset comprised Magnetic Resonance Imaging (MRI) scans of patients with BRAF fusion (n = 190), BRAF p.V600E mutation (n = 95), FGFR1 (n = 25), and other molecular subtypes (n = 144), while an...
Khashayar Namdar