Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach
Journal
NeuroImage
ISSN
1053-8119
Date Issued
2020
Author(s)
M. Belen Bachli
Lucas Sedeño
Jeremi K. Ochab
Olivier Piguet
Fiona Kumfor
Teresa Torralva
María Roca
Juan Felipe Cardona
Cecilia Gonzalez Campo
Eduar Herrera
Diana Matallana
Facundo Manes
Adolfo M. García
Agustín Ibáñez
Dante R. Chialvo
Type
Resource Types::text::journal::journal article
URL Institutional Repository
Subjects
alzheimer's disease
;
frontotemporal dementia
;
machine-learning
;
executive functions
;
voxel-based morphometry
;
classification
;
aged
;
aged, 80 and over
;
alzheimer disease
;
atrophy
;
biomarkers
;
executive function
;
female
;
frontotemporal dementia
;
humans
;
machine learning
;
magnetic resonance imaging
;
male
;
middle aged
;
neuropsychological tests
;
reproducibility of results
;
biological marker
;
aged
;
algorithm
;
alzheimer disease
;
article
;
brain atrophy
;
cognition
;
cognition assessment
;
diagnostic accuracy
;
disease classification
;
disease marker
;
early diagnosis
;
executive function
;
female
;
frontal variant frontotemporal dementia
;
human
;
machine learning
;
major clinical study
;
male
;
nuclear magnetic resonance imaging
;
prediction
;
priority journal
;
reliability
;
screening
;
voxel based morphometry
;
alzheimer disease
;
atrophy
;
clinical trial
;
executive function
;
frontotemporal dementia
;
machine learning
;
middle aged
;
multicenter study
;
neuropsychological test
;
pathology
;
pathophysiology
;
physiology
;
reproducibility
;
very elderly