Extracting High-Quality Features From Biomedical Datasets Using Multimodal Autoencoders
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Updated
Mar 20, 2019 - Python
Extracting High-Quality Features From Biomedical Datasets Using Multimodal Autoencoders
Interpretable TCGA-BRCA RNA-seq breast cancer subtype classification with ML, SHAP, pathway enrichment, and METABRIC external validation.
Transcriptomics-based METABRIC PAM50 breast cancer subtype classification with a reproducible Python ML pipeline.
Repository for CSC-690-003-2026S: Symbolic & Neuro-Symbolic AI, an independent study course.
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