Explainable machine learning identifies candidate shared neuroanatomical features in Alzheimer's and Parkinson's via importance inversion transfer
Daniele Caligiore, Simone Torsello, the Alzheimer’s Disease Neuroimaging Initiative
This paper introduces an explainable machine learning framework to identify shared neuroanatomical features between Alzheimer's and Parkinson's diseases, finding ten regional volumetric anchors with high diagnostic accuracy.
Scientific Reports · Sep 22, 2026Peer-reviewedNeuroscience