Francisco Jesús Martínez-Murcia
Orcid: 0000-0001-8146-7056
According to our database1,
Francisco Jesús Martínez-Murcia
authored at least 84 papers
between 2011 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
Statistical Agnostic Regression: a machine learning method to validate regression models.
CoRR, 2024
2023
Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends.
Inf. Fusion, December, 2023
Probabilistic Combination of Non-Linear Eigenprojections For Ensemble Classification.
IEEE Trans. Emerg. Top. Comput. Intell., October, 2023
Nonlinear Weighting Ensemble Learning Model to Diagnose Parkinson's Disease Using Multimodal Data.
Int. J. Neural Syst., August, 2023
Int. J. Neural Syst., April, 2023
Uncertainty-driven ensembles of multi-scale deep architectures for image classification.
Inf. Fusion, 2023
Integr. Comput. Aided Eng., 2023
EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia.
CoRR, 2023
Revealing Patterns of Symptomatology in Parkinson's Disease: A Latent Space Analysis with 3D Convolutional Autoencoders.
CoRR, 2023
2022
Complex network modeling of EEG band coupling in dyslexia: An exploratory analysis of auditory processing and diagnosis.
Knowl. Based Syst., 2022
Quantifying Differences Between Affine and Nonlinear Spatial Normalization of FP-CIT Spect Images.
Int. J. Neural Syst., 2022
Modelling the Progression of the Symptoms of Parkinsons Disease Using a Nonlinear Decomposition of 123I FP-CIT SPECT Images.
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
Temperature Control and Monitoring System for Electrical Power Transformers Using Thermal Imaging.
Proceedings of the Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence, 2022
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
Towards Mixed Mode Biomarkers: Combining Structural and Functional Information by Deep Learning.
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
Unraveling Dyslexia-Related Connectivity Patterns in EEG Signals by Holo-Hilbert Spectral Analysis.
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
Temporal Phase Synchrony Disruption in Dyslexia: Anomaly Patterns in Auditory Processing.
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
2021
Detecting Phase-Synchrony Connectivity Anomalies in EEG Signals. Application to Dyslexia Diagnosis.
Sensors, 2021
Statistical Agnostic Mapping: A framework in neuroimaging based on concentration inequalities.
Inf. Fusion, 2021
Deep residual transfer learning for automatic diagnosis and grading of diabetic retinopathy.
Neurocomputing, 2021
CoRR, 2021
Probabilistic combination of eigenlungs-based classifiers for COVID-19 diagnosis in chest CT images.
CoRR, 2021
Proceedings of the Advances in Computational Intelligence, 2021
Proceedings of the Bioengineering and Biomedical Signal and Image Processing, 2021
2020
Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders.
IEEE J. Biomed. Health Informatics, 2020
Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation.
Inf. Fusion, 2020
Granger causality-based information fusion applied to electrical measurements from power transformers.
Inf. Fusion, 2020
Autosomal dominantly inherited alzheimer disease: Analysis of genetic subgroups by machine learning.
Inf. Fusion, 2020
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications.
Neurocomputing, 2020
Neurocomputing, 2020
Dyslexia Diagnosis by EEG Temporal and Spectral Descriptors: An Anomaly Detection Approach.
Int. J. Neural Syst., 2020
EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia.
Int. J. Neural Syst., 2020
Morphological Characterization of Functional Brain Imaging by Isosurface Analysis in Parkinson's Disease.
Int. J. Neural Syst., 2020
Uncertainty-driven ensembles of deep architectures for multiclass classification. Application to COVID-19 diagnosis in chest X-ray images.
CoRR, 2020
A Neural Approach to Ordinal Regression for the Preventive Assessment of Developmental Dyslexia.
CoRR, 2020
Optimized One vs One Approach in Multiclass Classification for Early Alzheimer's Disease and Mild Cognitive Impairment Diagnosis.
IEEE Access, 2020
Dyslexia Detection from EEG Signals Using SSA Component Correlation and Convolutional Neural Networks.
Proceedings of the Hybrid Artificial Intelligent Systems - 15th International Conference, 2020
A Neural Approach to Ordinal Regression for the Preventive Assessment of Developmental Dyslexia.
Proceedings of the Hybrid Artificial Intelligent Systems - 15th International Conference, 2020
2019
Neurocomputing, 2019
Int. J. Neural Syst., 2019
Int. J. Neural Syst., 2019
Int. J. Neural Syst., 2019
Proceedings of the Understanding the Brain Function and Emotions, 2019
Proceedings of the Understanding the Brain Function and Emotions, 2019
Proceedings of the Understanding the Brain Function and Emotions, 2019
Comparison Between Affine and Non-affine Transformations Applied to I ^[123] [ 123 ] -FP-CIT SPECT Images Used for Parkinson's Disease Diagnosis.
Proceedings of the Understanding the Brain Function and Emotions, 2019
2018
Convolutional Neural Networks for Neuroimaging in Parkinson's Disease: Is Preprocessing Needed?
Int. J. Neural Syst., 2018
Using deep neural networks along with dimensionality reduction techniques to assist the diagnosis of neurodegenerative disorders.
Log. J. IGPL, 2018
Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease.
Frontiers Neuroinformatics, 2018
Proceedings of the International Joint Conference SOCO'18-CISIS'18-ICEUTE'18, 2018
Deep Convolutional Autoencoders vs PCA in a Highly-Unbalanced Parkinson's Disease Dataset: A DaTSCAN Study.
Proceedings of the International Joint Conference SOCO'18-CISIS'18-ICEUTE'18, 2018
Classification Improvement for Parkinson's Disease Diagnosis Using the Gradient Magnitude in DaTSCAN SPECT Images.
Proceedings of the International Joint Conference SOCO'18-CISIS'18-ICEUTE'18, 2018
Using Early Acquisitions of Amyloid-PET as a Surrogate of FDG-PET: A Machine Learning Based Approach.
Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018
2017
Frontiers Neuroinformatics, 2017
Functional Brain Imaging Synthesis Based on Image Decomposition and Kernel Modeling: Application to Neurodegenerative Diseases.
Frontiers Neuroinformatics, 2017
A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI.
Frontiers Neuroinformatics, 2017
A semi-supervised learning approach for model selection based on class-hypothesis testing.
Expert Syst. Appl., 2017
Case-Based Statistical Learning: A Non-Parametric Implementation With a Conditional-Error Rate SVM.
IEEE Access, 2017
Learning Longitudinal MRI Patterns by SICE and Deep Learning: Assessing the Alzheimer's Disease Progression.
Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017
Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017
Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017
Analysis of 18F-DMFP-PET data using Hidden Markov Random Field and the Gaussian distribution to assist the diagnosis of Parkinsonism.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Automatic Separation of Parkinsonian Patients and Control Subjects Based on the Striatal Morphology.
Proceedings of the Natural and Artificial Computation for Biomedicine and Neuroscience, 2017
Proceedings of the Natural and Artificial Computation for Biomedicine and Neuroscience, 2017
Case-Based Statistical Learning: A Non Parametric Implementation Applied to SPECT Images.
Proceedings of the Natural and Artificial Computation for Biomedicine and Neuroscience, 2017
On a Heavy-Tailed Intensity Normalization of the Parkinson's Progression Markers Initiative Brain Database.
Proceedings of the Natural and Artificial Computation for Biomedicine and Neuroscience, 2017
2016
A Structural Parametrization of the Brain Using Hidden Markov Models-Based Paths in Alzheimer's Disease.
Int. J. Neural Syst., 2016
Assisting the Diagnosis of Neurodegenerative Disorders Using Principal Component Analysis and TensorFlow.
Proceedings of the International Joint Conference SOCO'16-CISIS'16-ICEUTE'16, 2016
Magnetic resonance image classification using nonnegative matrix factorization and ensemble tree learning techniques.
Proceedings of the 18th IEEE International Workshop on Multimedia Signal Processing, 2016
2015
Neuroinformatics, 2015
A Volumetric Radial LBP Projection of MRI Brain Images for the Diagnosis of Alzheimer's Disease.
Proceedings of the Artificial Computation in Biology and Medicine, 2015
2014
Automatic detection of Parkinsonism using significance measures and component analysis in DaTSCAN imaging.
Neurocomputing, 2014
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2014
Proceedings of the Innovation in Medicine and Healthcare 2014, 2014
Multimodal image data fusion for Alzheimer's Disease diagnosis by sparse representation.
Proceedings of the Innovation in Medicine and Healthcare 2014, 2014
Proceedings of the Innovation in Medicine and Healthcare 2014, 2014
2013
LVQ-SVM based CAD tool applied to structural MRI for the diagnosis of the Alzheimer's disease.
Pattern Recognit. Lett., 2013
Application of Empirical Mode Decomposition (EMD) on DaTSCAN SPECT images to explore Parkinson Disease.
Expert Syst. Appl., 2013
Functional activity maps based on significance measures and Independent Component Analysis.
Comput. Methods Programs Biomed., 2013
Proceedings of the Natural and Artificial Computation in Engineering and Medical Applications, 2013
Proceedings of the Natural and Artificial Models in Computation and Biology, 2013
2012
Computer Aided Diagnosis tool for Alzheimer's Disease based on Mann-Whitney-Wilcoxon U-Test.
Expert Syst. Appl., 2012
2011
Analysis of Spect Brain Images Using Wilcoxon and Relative Entropy Criteria and Quadratic Multivariate Classifiers for the Diagnosis of Alzheimer's Disease.
Proceedings of the New Challenges on Bioinspired Applications, 2011