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Early prediction of Alzheimer's disease using null longitudinal model-based classifiers

Autor
Gavidia, G.; Kanaan-Izquierdo, S.; Mataro-Serrat, M.; Perera, A.
Tipus d'activitat
Article en revista
Revista
PloS one
Data de publicació
2017-01-03
Volum
12
Número
1
DOI
https://doi.org/10.1371/journal.pone.0168011 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/102451 Obrir en finestra nova
URL
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0168011 Obrir en finestra nova
Resum
Incipient Alzheimer’s Disease (AD) is characterized by a slow onset of clinical symptoms, with pathological brain changes starting several years earlier. Consequently, it is necessary to first understand and differentiate age-related changes in brain regions in the absence of disease, and then to support early and accurate AD diagnosis. However, there is poor understanding of the initial stage of AD; seemingly healthy elderly brains lose matter in regions related to AD, but similar changes can...
Citació
Gavidia, G., Kanaan, S., Mataro-Serrat, M., Perera, A. Early prediction of Alzheimer's disease using null longitudinal model-based classifiers. "PLoS one", 3 Gener 2017, vol. 12, núm. 1.
Paraules clau
Alzheimer disease, Atrophy, Biomarkers, Cerebrospinal fluid, Cognitive impairment, Linear Mixed Effect Modelling, Magnetic resonance imaging, Neuropsychological testing, Support vector machines
Grup de recerca
B2SLab - Bioinformatics and Biomedical Signals Laboratory
CREB - Centre de Recerca en Enginyeria Biomedica
TALP - Centre de Tecnologies i Aplicacions del Llenguatge i la Parla

Participants