ListarIC - Artículos por tema "Alzheimer’s disease"

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Empirical Functional PCA for 3D Image Feature Extraction Through Fractal Sampling.

Ortiz-García, Andrés; Munilla-Fajardo, Jorge; Martínez-Murcia, Francisco Jesús; Górriz-Sáez, Juan Manuel; Ramírez-Aguilar, Francisco Javier (World Scientific, 2018-10-16)

Medical image classification is currently a challenging task that can be used to aid the diagnosis of different brain diseases. Thus, exploratory and discriminative analysis techniques aiming to obtain representative ...
Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

Ramírez, Javier; Górriz-Sáez, Juan Manuel; Ortiz-García, Andrés; Martínez-Murcia, Francisco Jesús; Segovia, Fermín; Salas-González, Diego; Castillo-Barnes, Diego; Álvarez-Illán, Ignacio; Puntonet, Carlos[et al.] (Elsevier, 2017-12-11)

Background: Alzheimer’s disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of ...
Ensembling shallow siamese architectures to assess functional asymmetry in Alzheimer’s disease progression.

Arco, Juan E.; Ortiz-García, Andrés; Castillo-Barnes, Diego; Górriz-Sáez, Juan Manuel; Ramírez, Javier (Elsevier, 2023-01-06)

The development of methods based on artificial intelligence for the classification of medical imaging is widespread. Given the high dimensionality of this type of images, it is imperative to use the information contained ...
Studying the Manifold Structure of Alzheimer’s Disease: A Deep Learning Approach Using Convolutional Autoencoders

Martínez-Murcia, Francisco Jesús; Ortiz-García, Andrés; Górriz-Sáez, Juan Manuel; Ramírez, Javier; Castillo-Barnes, Diego (IEEE, 2020-01-01)

Many classical machine learning techniques have been used to explore Alzheimer’s Disease, evolving from image decomposition techniques such as Principal Component Analysis towards higher-complexity, non-linear decomposition ...
Using XAI in the Clock Drawing Test to reveal the cognitive impairment pattern.

Jiménez-Mesa, Carmen; Arco, Juan E.; Valentí-Soler, Meritxell; Frades-Payo, Belén; Zea-Sevilla, María A.; Ortiz-García, Andrés; Ávila-Villanueva, Marina; Castillo-Barnes, Diego; Ramírez, Javier; Del-Ser-Quijano, Teodoro; Carnero Pardo, Cristóbal; Górriz-Sáez, Juan Manuel[et al.] (World Scientific, 2023-02-16)

he prevalence of dementia is currently increasing worldwide. This syndrome produces a deteriorationin cognitive function that cannot be reverted. However, an early diagnosis can be crucial for slowing itsprogress. The Clock ...

ListarIC - Artículos por tema "Alzheimer’s disease"

Empirical Functional PCA for 3D Image Feature Extraction Through Fractal Sampling. ﻿

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares. ﻿

Ensembling shallow siamese architectures to assess functional asymmetry in Alzheimer’s disease progression. ﻿

Studying the Manifold Structure of Alzheimer’s Disease: A Deep Learning Approach Using Convolutional Autoencoders ﻿

Using XAI in the Clock Drawing Test to reveal the cognitive impairment pattern. ﻿

Empirical Functional PCA for 3D Image Feature Extraction Through Fractal Sampling.

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

Ensembling shallow siamese architectures to assess functional asymmetry in Alzheimer’s disease progression.

Studying the Manifold Structure of Alzheimer’s Disease: A Deep Learning Approach Using Convolutional Autoencoders

Using XAI in the Clock Drawing Test to reveal the cognitive impairment pattern.