Article

Integrative Unsupervised and Supervised Learning Approaches for Breast Cancer Subtype Classification Using Gene Expression Data

2025-04-29

Abstract excerpt

Breast cancer is a heterogeneous disease with distinct molecular subtypes that require precise classification for personalized treatment strategies. This study proposes an integrative methodology combining unsupervised and supervised learning techniques (hybrid learning) to classify breast cancer subtypes using gene expression data from the Gene Expression Omnibus (GEO) repository. Hierarchical clustering is emplo...

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Literature Corpus work: bd76dc13-6e99-5bb5-bdb0-bbd2661a0e50
DOI: 10.20944/preprints202504.2451.v1

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