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Article

Generative AI in glioma: Ensuring diversity in training image phenotypes to improve diagnostic performance for IDH mutation prediction.

Neuro-oncology - 3 Jun 2024

Moon Hye Hyeon, Jeong Jiheon, Park Ji Eun, Kim Namkug, Choi Changyong, Kim Young-Hoon, Song Sang Woo, Hong Chang-Ki, Kim Jeong Hoon, Kim Ho Sung

Abstract excerpt

BACKGROUND: This study evaluated whether generative artificial intelligence (AI)-based augmentation (GAA) can provide diverse and realistic imaging phenotypes and improve deep learning-based classification of isocitrate dehydrogenase (IDH) type in glioma compared with neuroradiologists. METHODS: For model development, 565 patients (346 IDH-wildtype, 219 IDH-mutant) with paired contrast-enhanced T1 and FLAIR MRI...

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Identifiers

PMID: 38253989
DOI: 10.1093/neuonc/noae012
PMCID: PMC11145451

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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