Classification of Healthy Subjects and Alzheimer's Disease Patients with Dementia from Cortical Sources of Resting State EEG Rhythms: A Study Using Artificial Neural Networks

Previous evidence showed a 75.5% best accuracy in the classification of 120 Alzheimer's disease (AD) patients with dementia and 100 matched normal elderly (Nold) subjects based on cortical source current density and linear lagged connectivity estimated by eLORETA freeware from resting state eye...

Πλήρης περιγραφή

Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Τόπος έκδοσης:Front Neurosci
Κύριοι συγγραφείς: Triggiani, Antonio I., Bevilacqua, Vitoantonio, Brunetti, Antonio, Lizio, Roberta, Tattoli, Giacomo, Cassano, Fabio, Soricelli, Andrea, Ferri, Raffaele, Nobili, Flavio, Gesualdo, Loreto, Barulli, Maria R., Tortelli, Rosanna, Cardinali, Valentina, Giannini, Antonio, Spagnolo, Pantaleo, Armenise, Silvia, Stocchi, Fabrizio, Buenza, Grazia, Scianatico, Gaetano, Logroscino, Giancarlo, Lacidogna, Giordano, Orzi, Francesco, Buttinelli, Carla, Giubilei, Franco, Del Percio, Claudio, Frisoni, Giovanni B., Babiloni, Claudio
Μορφή: Artigo
Γλώσσα:Inglês
Έκδοση: Frontiers Media S.A. 2017
Θέματα:
Neuroscience
Διαθέσιμο Online:https://ncbi.nlm.nih.gov/pmc/articles/PMC5266711/
https://ncbi.nlm.nih.gov/pubmed/28184183
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2016.00604
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