Litcius/Paper detail

Stacked autoencoders as new models for an accurate Alzheimer’s disease classification support using resting-state EEG and MRI measurements

Raffaele Ferri, Claudio Babiloni, Vania Karami, Antonio Ivano Triggiani, Filippo Carducci, Giuseppe Noce, Roberta Lizio, Maria Teresa Pascarelli, Andrea Soricelli, Francesco Amenta, Alessandro Bozzao, Andrea Romano, Franco Giubilei, Claudio Del Percio, Fabrizio Stocchi, Giovanni B. Frisoni, Flavio Nobili, Luca Patané, Paolo Arena

2020Clinical Neurophysiology58 citationsDOIOpen Access PDF

Topics & Concepts

Resting state fMRIElectroencephalographyPattern recognition (psychology)NeuroscienceArtificial intelligenceDiseaseComputer sciencePsychologyMedicinePathologyFunctional Brain Connectivity StudiesEEG and Brain-Computer InterfacesNeural dynamics and brain function
Stacked autoencoders as new models for an accurate Alzheimer’s disease classification support using resting-state EEG and MRI measurements | Litcius