Author: Solano-Rojas, Braulio; Villalón-Fonseca, Ricardo; MarÃn-Raventós, Gabriela
Title: Alzheimer’s Disease Early Detection Using a Low Cost Three-Dimensional Densenet-121 Architecture Cord-id: dffnvxnf Document date: 2020_5_31
ID: dffnvxnf
Snippet: The objective of this work is to detect Alzheimer’s disease using Magnetic Resonance Imaging. For this, we use a three-dimensional densenet-121 architecture. With the use of only freely available tools, we obtain good results: a deep neural network showing metrics of 87% accuracy, 87% sensitivity (micro-average), 88% specificity (micro-average), and 92% AUROC (micro-average) for the task of classifying five different classes (disease stages). The use of tools available for free means that this
Document: The objective of this work is to detect Alzheimer’s disease using Magnetic Resonance Imaging. For this, we use a three-dimensional densenet-121 architecture. With the use of only freely available tools, we obtain good results: a deep neural network showing metrics of 87% accuracy, 87% sensitivity (micro-average), 88% specificity (micro-average), and 92% AUROC (micro-average) for the task of classifying five different classes (disease stages). The use of tools available for free means that this work can be replicated in developing countries.
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