CA-CAE: A deep learning-based multi-omics model for pan-cancer subtype classification and prognosis prediction
Fig 8
Overview of CA-CAE: The model includes feature normalization, dimensionality reduction, feature selection, and survival analysis for three types of omics data (DNA methylation, mRNA-seq, and miRNA-seq).
Each omics dataset is modeled with a convolutional autoencoder (CAE) combined with an attention mechanism to improve flexibility and scalability for heterogeneous data types.