Listar por autor "Martínez-Murcia, Francisco Jesús"
Mostrando ítems 1-16 de 16
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Assessing Functional Brain Network Dynamics in Dyslexia From fNIRS Data
Gallego-Molina, Nicolás J.; Ortiz-García, Andrés
; Martínez-Murcia, Francisco Jesús; Rodríguez-Rodríguez, Ignacio; Luque-Vilaseca, Juan Luis (World Scientific, 2023-01-09)
Developmental dyslexia is characterized by a deficit of phonological awareness whose origin is related to atypical neural processing of speech streams. This can lead to differences in the neural networks that encode audio ... -
Autosomal Dominantly Inherited Alzheimer Disease: Analysis of genetic subgroups by Machine Learning.
Castillo-Barnes, Diego; Li, Su; Ramírez-Aguilar, Francisco Javier; Salas-González, Diego; Martínez-Murcia, Francisco Jesús; Álvarez-Illán, Ignacio; Segovia, Fermín; Ortiz-García, Andrés; Cruchaga, Carlos; Farlow, Martin R.; Xiong, Chengjie; Graff-Radford, Neil R.; Schofield, Peter R.; Masters, Colin L.; Salloway, Stephen; Jucker, Mathias; Mori, Hiroshi; Levin, Johannes; Górriz-Sáez, Juan Manuel[et al.] (Elsevier, 2020-01-07)
Despite subjects with Dominantly-Inherited Alzheimer’s Disease (DIAD) represent less than 1% of all Alzheimer’s Disease (AD) cases, the Dominantly Inherited Alzheimer Network (DIAN) initiative constitutes a strong impact ... -
Complex network modelling of EEG band coupling in dyslexia: An exploratory analysis of auditory processing and diagnosis
Gallego-Molina, Nicolás J.; Ortiz-García, Andrés; Martínez-Murcia, Francisco Jesús; Giménez-de-la-Peña, Almudena; Formoso, Marco A. (Elsevier, 2022-01-05)
Complex network analysis has an increasing relevance in the study of neurological disorders, enhancing the knowledge of brain’s structural and functional organization. Network structure and efficiency reveal different ... -
Deep Residual Transfer Learning for Automatic Diabetic Retinopathy Grading.
Martínez-Murcia, Francisco Jesús; Ortiz-García, Andrés; Ramírez-Aguilar, Francisco Javier; Górriz-Sáez, Juan Manuel; Cruz, Ricardo (Elsevier, 2021-09-10)
Evaluation and diagnosis of retina pathology is usually made via the analysis of different image modalities that allow to explore its structure. The most popular retina image method is retinography, a technique that displays ... -
Discriminative Sparse Features for Alzheimer’s Disease Diagnosis using multimodal image data.
Ortiz-García, Andrés; Lozano Cuadra, Federico; Górriz-Sáez, Juan Manuel; Ramírez-Aguilar, Francisco Javier; Martínez-Murcia, Francisco Jesús (Bentham Science, 2018-01-01)
Feature extraction in medical image processing still remains a challenge, especially in high-dimensionality datasets, where the expected number of available samples is considerably lower than the dimension of the feature ... -
Dyslexia Diagnosis by EEG Temporal and Spectral Descriptors: An Anomaly Detection Approach.
Ortiz-García, Andrés; Martínez-Murcia, Francisco Jesús; Luque-Vilaseca, Juan Luis; Giménez-de-la-Peña, Almudena; Morales-Ortega, Roberto; Ortega, Julio[et al.] (World Scientific, 2020-06-04)
Diagnosis of learning difficulties is a challenging goal. There are huge number of factors involved in the evaluation procedure that present high variance among the population with the same difficulty. Diagnosis is usually ... -
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 ... -
Enhancing Neuronal Coupling Estimation by NIRS/EEG Integration.
Gallego-Molina, Nicolás J.; Ortiz-García, Andrés; Formoso, Marco A.; Martínez-Murcia, Francisco Jesús; Woo, Wai Lok (2024)
Neuroimaging techniques have had a major impact on medical science, allowing advances in the research of many neurological diseases and improving their diagnosis. In this context, multimodal neuroimaging approaches, based ... -
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 ... -
Granger Causality-based Information Fusion Applied to Electrical Measurements from Power Transformers.
Rodríguez-Rivero, Jacob; Ramírez, Javier; Martínez-Murcia, Francisco Jesús; Segovia, Fermín; Ortiz-García, Andrés; Salas-González, Diego; Castillo-Barnes, Diego; Álvarez-Illán, Ignacio; Puntonet, Carlos; Jiménez-Mesa, Carmen; Leiva, Francisco J.; Carrillo, Susana; Suckling, John; Górriz-Sáez, Juan Manuel[et al.] (Elsevier, 2019-05-01)
In the immediate future, with the increasing presence of electrical vehicles and the large increase in the use of renewable energies, it will be crucial that distribution power networks are managed, supervised and exploited ... -
Label Aided Deep Ranking for the Automatic Diagnosis of Parkinsonian Syndromes.
Ortiz-García, Andrés; Martínez-Murcia, Francisco Jesús; Munilla-Fajardo, Jorge; Górriz-Sáez, Juan Manuel; Ramírez, Javier (Elsevier, 2018-10-16)
Parkinsonism is the second most common neurodegenerative disease in the world. Its diagnosis usually relies on visual analysis of Emission Computed Tomography (SPECT) images acquired using 123I − io f lupane radiotracer. ... -
¡Las máquinas nos quitan el trabajo! Una introducción a la inteligencia artificial y al deep learning
(2019-07-30)Cada vez aparecen más soluciones tecnológicas que hacen a las máquinas más inteligentes, por lo que el miedo a que nos quiten el trabajo aflora con frecuencia. En esta charla explicaremos como funcionan algunos sistemas ... -
Probabilistic Combination of Non-Linear Eigenprojections For Ensemble Classification.
Arco, Juan E.; Ortiz-García, Andrés; Ramírez, Javier; Martínez-Murcia, Francisco Jesús; Zhang, Yu-Dong; Broncano, Jordi; Berbís, Álvaro; Royuela-del-Val, Javier; Luna, Antonio; Górriz-Sáez, Juan Manuel[et al.] (IEEE, 2022-10-10)
The emergence of new technologies has changed the way clinicians perform diagnosis. Medical imaging play a crucial role in this process, given the amount of information that they usually provide as non-invasive techniques. ... -
Statistical Agnostic Mapping: A framework in neuroimaging based on concentration inequalities.
Górriz-Sáez, Juan Manuel; Jiménez-Mesa, Carmen; Romero-García, Raúl; Segovia, Fermín; Ramírez, Javier; Castillo-Barnes, Diego; Martínez-Murcia, Francisco Jesús; Ortiz-García, Andrés; Salas-González, Diego; Álvarez-Illán, Ignacio; Puntonet, Carlos; López-García, Diego; Gómez-Río, Manuel; Suckling, John[et al.] (Elsevier, 2020-09-26)
In the 1970s a novel branch of statistics emerged focusing its effort on the selection of a function for the pattern recognition problem that would fulfill a relationship between the quality of the approximation and ... -
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 ... -
Temporal phase synchrony disruption in dyslexia: anomaly patterns in auditory processing
Formoso, Marco A.; Ortiz-García, Andrés; Martínez-Murcia, Francisco Jesús; Aquino Brítez, Diego; Escobar, Juan José; Luque-Vilaseca, Juan Luis[et al.] (2022)
The search for a dyslexia diagnosis based on exclusively objective methods is currently a challenging task. Usually, this disorder is analyzed by means of behavioral tests prone to errors due to their subjective nature; ...