Researchers from Soonchunhyang University have developed artificial intelligence models that enable noninvasive identification of pathogenic variants in central nervous system tumors. These models integrate genetic data from cerebrospinal fluid and imaging data from MRI scans, enhancing tumor type classification and mutation detection accuracy. Presented at the AMP annual meeting, findings demonstrate improved diagnostic robustness, supporting earlier intervention and personalized treatment while reducing the need for invasive biopsies. Dr. Jieun Kim led this pivotal research.
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