SNUH methylation classifier for CNS tumors.

ABSTRACT:

Background

Methylation profiling of central nervous system (CNS) tumors, pioneered by the German Cancer Research Center, has significantly improved diagnostic accuracy. This study aimed to further enhance the performance of methylation classifiers by leveraging publicly available data and innovative machine-learning techniques.

Results

Seoul National University Hospital Methylation Classifier (SNUH-MC) addressed data imbalance using the Synthetic Minority Over-sampling Technique (SMOTE) algorithm and incorporated OpenMax within a Multi-Layer Perceptron to prevent labeling errors in low-confidence diagnoses. Compared to two published CNS tumor methylation classification models (DKFZ-MC: Deutsches Krebsforschungszentrum Methylation Classifier v11b4: RandomForest, 767-MC: Multi

SUBMITTER: Lee K 

PROVIDER: S-EPMC11905536 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature