Abstract
The increasing complexity of neurological disorders, characterized by heterogeneous pathophysiology and variable clinical outcomes, presents significant challenges for accurate diagnosis and personalized treatment. Traditional approaches often fail to capture the dynamic and individualized nature of brain disorders, limiting the effectiveness of therapeutic strategies. In this context, digital twin technology has emerged as a novel paradigm in precision medicine, enabling the creation of virtual, patient-specific models that replicate biological systems and disease processes.
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