Quantum-Inspired Variational Optimization of neuromorphic self-supervised heterogeneous graph transformers for multimodal Parkinson’s disease representation learning
Early diagnosis of Parkinson’s disease (PD) remains challenging due to the heterogeneous nature of multimodal clinical data, limited annotated datasets, suboptimal multimodal fusion strategies, and the absence of uncertainty-aware decision-making in existing deep learning models. This paper proposes NeuroQ-MGST, a Neur...
Tarak Hussain, Bal Virdee, Irfan Alam et al.
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