TY  - JOUR 
AU  - Agarwal, Deevyankar
AU  - Berbís, Manuel Álvaro
AU  - Martín Noguerol, Teodoro
AU  - Luna, Antonio
AU  - García Parrado, Sara Carmen
AU  - Torre Díez, Isabel de la
PY  - 2022
SN  - 2227-7390
UR  - https://uvadoc.uva.es/handle/10324/61987
AB  - This study uses magnetic resonance imaging (MRI) data to propose end-to-end learning implementing volumetric convolutional neural network (CNN) models for two binary classification tasks: Alzheimer’s disease (AD) vs. cognitively normal (CN) and stable...
LA  - eng
PB  - MDPI
KW  - Brain - Diseases
KW  - Cerebro - Enfermedades
KW  - Alzheimer's disease
KW  - Alzheimer's disease - Diagnosis
KW  - Alzheimer, Enfermedad de
KW  - Neural networks (Computer science)
KW  - Convolutional neural network
KW  - Redes neuronales (Informática)
KW  - Machine learning
KW  - Aprendizaje automático
KW  - Artificial intelligence
KW  - Mild cognitive impairment
KW  - Magnetic resonance imaging
KW  - Resonancia magnética
KW  - Neurology
KW  - Neuroimaging
KW  - Image processing
KW  - Imágenes, Tratamiento de las
TI  - End-to-end deep learning architectures using 3D neuroimaging biomarkers for early Alzheimer’s diagnosis
DO  - 10.3390/math10152575
ER  -