Novel applications of machine learning and computational neuroscience models to neuroimaging in Parkinson’s disease and related disorders

Computational approaches enhance the diagnosis of Parkinsonian syndromes, particularly in the early stages, and refine the characterization of disease subtypes, benefiting clinicians, especially in non-expert centers. Such applications hold significant potential for enabling more personalized management and selecting appropriate candidates for clinical trials. Furthermore, a deeper understanding of pathophysiology supports the development of disease-specific therapies.