Glioma Image-Level and Slide-Level Gene Predictor (GLISP) for Molecular Diagnosis and Predicting Genetic Events of Adult Diffuse Glioma.

ABSTRACT: The latest World Health Organization (WHO) classification of central nervous system tumors (WHO2021/5th) has incorporated molecular information into the diagnosis of each brain tumor type including diffuse glioma. Therefore, an artificial intelligence (AI) framework for learning histological patterns and predicting important genetic events would be useful for future studies and applications. Using the concept of multiple-instance learning, we developed an AI framework named GLioma Image-level and Slide-level gene Predictor (GLISP) to predict nine genetic abnormalities in hematoxylin and eosin sections: IDH1/2, ATRX, TP53 mutations, TERT promoter mutations, CDKN2A/B homozygous deletion (CHD), EGFR amplification (EGFRamp), 7 gain/10 loss (7+/1

SUBMITTER: Le MK 

PROVIDER: S-EPMC11761954 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature