A fused deep learning approach to transform drug repositioning

This work presents a fused deep learning framework for drug repositioning. By integrating heterogeneous biomedical signals within a unified predictive architecture, the study improves prioritization of repurposing candidates and expands the applicability of deep learning to data-sparse repositioning scenarios.