Aimpact-X: A Causally-Grounded Interpretable Multimodal Deep Learning Framework for Transparent Early Disease Detection Using Imaging, Clinical, And Genomic Data
Recent developments in multimodal deep learning have brought great progress to early disease detection; yet, wide-scale implementation of such models in clinics is hindered by the inherently inscrutable reasoning of existing methods. Current frameworks often employ post-hoc explanations that are not cross-modal consist...