Carmen Jimenez-Mesa
Orcid: 0000-0003-2494-2951
According to our database1,
Carmen Jimenez-Mesa authored at least 27 papers
between 2020 and 2026.
Collaborative distances:
Collaborative distances:
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Bibliography
2026
DualFlexKAN: Dual-stage Kolmogorov-Arnold Networks with Independent Function Control.
CoRR, March, 2026
An explainable framework for the relationship between dementia and glucose metabolism patterns.
CoRR, January, 2026
An explainable framework for the relationship between dementia and metabolism patterns.
NeuroImage, 2026
Longitudinal Modeling of Alzheimer's Disease Progression Using a Bayesian Latent Framework with APOE-Dependent Genetic Effects.
Proceedings of the Artificial Intelligence for Neuroscience, Mental Health, and Neurodegenerative Disorders, 2026
Proceedings of the Artificial Intelligence for Neuroscience, Mental Health, and Neurodegenerative Disorders, 2026
From Regions to Manifolds: Linking Radiomic Signatures with PCA and UMAP Brain Representations in Glioma.
Proceedings of the Artificial Intelligence for Neuroscience, Mental Health, and Neurodegenerative Disorders, 2026
2025
CoRR, July, 2025
2024
Bridging Imaging and Clinical Scores in Parkinson's Progression via Multimodal Self-Supervised Deep Learning.
Int. J. Neural Syst., August, 2024
Statistical Agnostic Regression: a machine learning method to validate regression models.
CoRR, 2024
A Cross-Modality Latent Representation for the Prediction of Clinical Symptomatology in Parkinson's Disease.
Proceedings of the Artificial Intelligence for Neuroscience and Emotional Systems, 2024
A Comparative Study of Deep Learning Approaches for Cognitive Impairment Diagnosis Based on the Clock-Drawing Test.
Proceedings of the Artificial Intelligence for Neuroscience and Emotional Systems, 2024
2023
Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends.
Inf. Fusion, December, 2023
Nonlinear Weighting Ensemble Learning Model to Diagnose Parkinson's Disease Using Multimodal Data.
Int. J. Neural Syst., August, 2023
Using Explainable Artificial Intelligence in the Clock Drawing Test to Reveal the Cognitive Impairment Pattern.
Int. J. Neural Syst., April, 2023
A non-parametric statistical inference framework for Deep Learning in current neuroimaging.
Inf. Fusion, 2023
Revealing Patterns of Symptomatology in Parkinson's Disease: A Latent Space Analysis with 3D Convolutional Autoencoders.
CoRR, 2023
2022
A Connection Between Pattern Classification by Machine Learning and Statistical Inference With the General Linear Model.
IEEE J. Biomed. Health Informatics, 2022
Quantifying Differences Between Affine and Nonlinear Spatial Normalization of FP-CIT Spect Images.
Int. J. Neural Syst., 2022
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
Automatic Classification System for Diagnosis of Cognitive Impairment Based on the Clock-Drawing Test.
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
Evaluating Intensity Concentrations During the Spatial Normalization of Functional Images for Parkinson's Disease.
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
CAD System for Parkinson's Disease with Penalization of Non-significant or High-Variability Input Data Sources.
Proceedings of the Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications, 2022
2021
Statistical Agnostic Mapping: A framework in neuroimaging based on concentration inequalities.
Inf. Fusion, 2021
Deep Learning in current Neuroimaging: a multivariate approach with power and type I error control but arguable generalization ability.
CoRR, 2021
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
Optimized One vs One Approach in Multiclass Classification for Early Alzheimer's Disease and Mild Cognitive Impairment Diagnosis.
IEEE Access, 2020