A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease

A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease

Inglese et al. develop a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted magnetic resonance imaging scans. Their model reliably discriminates people with Alzheimer’s disease-related pathologies from those without.

Bibliographic Details
Main Authors: Marianna Inglese, Neva Patel, Kristofer Linton-Reid, Flavia Loreto, Zarni Win, Richard J. Perry, Christopher Carswell, Matthew Grech-Sollars, William R. Crum, Haonan Lu, Paresh A. Malhotra, the Alzheimer’s Disease Neuroimaging Initiative, Eric O. Aboagye
Format: Article
Language:English
Published: Nature Portfolio 2022-06-01
Series:Communications Medicine
Online Access:https://doi.org/10.1038/s43856-022-00133-4

Internet

https://doi.org/10.1038/s43856-022-00133-4

Similar Items