Glioma Grade and Molecular Markers: Comparing Machine-Learning Approaches Using VASARI (Visually AcceSAble Rembrandt Images) Radiological Assessment

This study aimed to leverage Visually AcceSAble Rembrandt Images (VASARI) radiological features, extracted from magnetic resonance imaging (MRI) scans, and machine-learning techniques to predict glioma grade, isocitrate dehydrogenase (IDH) mutation status, and O6-methylguanine-DNA methyltransferase...

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Veröffentlicht in:	Curēus (Palo Alto, CA) CA), 2024-07, Vol.16 (7), p.e63873
Hauptverfasser:	Setyawan, Nurhuda H, Choridah, Lina, Nugroho, Hanung A, Malueka, Rusdy G, Dwianingsih, Ery K, Supriatna, Yana, Supriyadi, Bambang, Hartanto, Rachmat A
Format:	Artikel
Sprache:	eng
Schlagworte:	Brain cancer Brain research Chemotherapy Classification Decision trees Dehydrogenases Glioma Healthcare Technology Machine learning Magnetic resonance imaging Medical prognosis Mutation Nervous system Oncology Patients Performance evaluation Radiology Software Tumors
Online-Zugang:	Volltext
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