Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging

Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. We hypothesized that the application of these algorithms to 18 F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) may help in diagnosis of Alzheimer’s disea...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Frontiers in aging neuroscience Jg. 13; S. 708932
Hauptverfasser:	Díaz-Álvarez, Josefa, Matias-Guiu, Jordi A., Cabrera-Martín, María Nieves, Pytel, Vanesa, Segovia-Ríos, Ignacio, García-Gutiérrez, Fernando, Hernández-Lorenzo, Laura, Matias-Guiu, Jorge, Carreras, José Luis, Ayala, José L.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media S.A 03.02.2022
Schlagworte:	Aging Neuroscience Alzheimer’s disease frontotemporal dementia machine learning positron emission tomography primary progressive aphasia unsupervised algorithm genetic algorithm Alzheimer’s disease frontotemporal dementia unsupervised algorithm machine learning positron emission tomography evolutionary algorithm primary progressive aphasia
ISSN:	1663-4365, 1663-4365
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!