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...

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Vydané v:	Frontiers in aging neuroscience Ročník 13; s. 708932
Hlavní autori:	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.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Media S.A 03.02.2022
Predmet:	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
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