When Clinical and Metabolomics Data Work Together: A Comparative Framework for Multimodal Disease Classification across Machine and Deep Learning
A modality-aware comparative framework that enables direct, side-by-side evaluation of clinical-only, metabolomics-only, and combined modeling strategies within a unified pipeline, and reveals that the dominant contributing modality shifted by scenario, reflecting differences in disease context.