Ahmed M. Shalaby

Parkinson's disease and essential tremor look alike early, with misdiagnosis rates of 20% to 30% even at specialized clinics, and the white-matter tracts mapped by conventional diffusion tensor imaging do not capture microstructural change inside gray matter. The study instead builds diffusion similarity networks, linking brain regions by the statistical similarity of their diffusion profiles, then filters connections with iterative permutation sampling recursive feature elimination and classifies with a graph neural network. In five-fold cross-validation on a local cohort of 100 people, the pipeline separated Parkinson's disease from essential tremor with an AUC of 0.94, and on a separate 40-person hold-out set it reached 87.5% balanced accuracy.

Parkinson's disease and essential tremor look alike early, with misdiagnosis rates of 20% to 30% even at specialized clinics, and the white-matter tracts mapped by conventional diffusion tensor imaging do not capture microstructural change inside gray matter. The study instead builds diffusion similarity networks, linking brain regions by the statistical similarity of their diffusion profiles, then filters connections with iterative permutation sampling recursive feature elimination and classifies with a graph neural network. In five-fold cross-validation on a local cohort of 100 people, the pipeline separated Parkinson's disease from essential tremor with an AUC of 0.94, and on a separate 40-person hold-out set it reached 87.5% balanced accuracy.