Integrative Machine Learning Framework for Enhanced Subgroup Classification in Medulloblastoma.

Journal: Healthcare (Basel, Switzerland)
Published Date: May 11, 2025

Abstract

BACKGROUND: Medulloblastoma is the most common malignant brain tumor in children, classified into four primary molecular subgroups: WNT, SHH, Group 3, and Group 4, each exhibiting significant molecular heterogeneity and varied survival outcomes. Accurate classification of these subgroups is crucial for optimizing treatments and improving patient outcomes. DNA methylation profiling is a promising approach for subgroup classification; however, its application is still evolving, with ongoing efforts to improve accessibility and develop more accurate classification methods.

Authors

  • Kaung Htet Hein
    School of Electronics, Electrical Engineering, and Computer Science, Queen's University Belfast, Belfast BT9 5BN, UK.
  • Wai Lok Woo
    School of Engineering, University of Newcastle upon Tyne, Newcastle upon Tyne, U.K.
  • Gholamreza Rafiee
    School of Electronics, Electrical Engineering, and Computer Science, Queen's University Belfast, Belfast BT9 5BN, UK.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals