Prognostically Relevant Subtypes and Survival Prediction for Breast Cancer Based on Multimodal Genomics Data

This implementation uses a Multimodal Autoencoder with Deep Belief Networks to analyze TCGA breast cancer genomics data (DNA methylation, gene expression, miRNA). It predicts cancer subtypes (ER/PR/HER2) and patient survival rates, providing a configurable pipeline for precision oncology research. (348 characters)