132 citations · 664 across the 24 of their papers we have counts for
24 papers
Influence of Autoencoder Latent Space on Classifying IoT CoAP Attacks
María Teresa García-Ordás, Jose Aveleira-Mata, Isaías García-Rodríguez +3
The Internet of Things (IoT) presents a unique cybersecurity challenge due to its vast network of interconnected, resource-constrained devices. These vulnerabilities not only threa…
Classification of Psychiatry Clinical Notes by Diagnosis: A Deep Learning and Machine Learning Approach
Sergio Rubio-Martín, María Teresa García-Ordás, Antonio Serrano-García +3
The classification of clinical notes into specific diagnostic categories is critical in healthcare, especially for mental health conditions like Anxiety and Adjustment Disorder. In…
TEDNet: Twin Encoder Decoder Neural Network for 2D Camera and LiDAR Road Detection
Martín Bayón-Gutiérrez, María Teresa García-Ordás, Héctor Alaiz Moretón +3
Robust road surface estimation is required for autonomous ground vehicles to navigate safely. Despite it becoming one of the main targets for autonomous mobility researchers in rec…
Enhancing ASD detection accuracy: a combined approach of machine learning and deep learning models with natural language processing
Sergio Rubio-Martín, María Teresa García-Ordás, Martín Bayón-Gutiérrez +2
Purpose: Our study explored the use of artificial intelligence (AI) to diagnose autism spectrum disorder (ASD). It focused on machine learning (ML) and deep learning (DL) to detect…
Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19
María Teresa García-Ordás, Natalia Arias, Carmen Benavides +2
COVID-19 disease has affected almost every country in the world. The large number of infected people and the different mortality rates between countries has given rise to many hypo…
Feasibility of Social-Network-Based eHealth Intervention on the Improvement of Healthy Habits among Children
José Alberto Benítez-Andrades, Natalia Arias, María Teresa García-Ordás +2
This study shows the feasibility of an eHealth solution for tackling eating habits and physical activity in the adolescent population. The participants were children from 11 to 15…
Middleware-based multi-agent development environment for building and testing distributed intelligent systems
Francisco José Aguayo-Canela, Héctor Alaiz-Moretón, María Teresa García-Ordás +4
The spread of the Internet of Things (IoT) is demanding new, powerful architectures for handling the huge amounts of data produced by the IoT devices. In many scenarios, many exist…
Enriched multi-agent middleware for building rule-based distributed security solutions for IoT environments
Francisco José Aguayo-Canela, Héctor Alaiz-Moretón, María Teresa García-Ordás +3
The increasing number of connected devices and the complexity of Internet of Things (IoT) ecosystems are demanding new architectures for managing and securing these networked envir…
Detection of the most influential variables for preventing postpartum urinary incontinence using machine learning techniques
José Alberto Benítez-Andrades, María Teresa García-Ordás, María Álvarez-González +2
Background: Postpartum urinary incontinence (PUI) is a common issue among postnatal women. Previous studies identified potential related variables, but lacked analysis on certain i…
Implementing local-explainability in Gradient Boosting Trees: Feature Contribution
Ángel Delgado-Panadero, Beatriz Hernández-Lorca, María Teresa García-Ordás +1
Gradient Boost Decision Trees (GBDT) is a powerful additive model based on tree ensembles. Its nature makes GBDT a black-box model even though there are multiple explainable artifi…
Clustering Techniques Selection for a Hybrid Regression Model: A Case Study Based on a Solar Thermal System
María Teresa García-Ordás, Héctor Alaiz-Moretón, José-Luis Casteleiro-Roca +5
This work addresses the performance comparison between four clustering techniques with the objective of achieving strong hybrid models in supervised learning tasks. A real dataset…
Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)-Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study
José Alberto Benítez-Andrades, José-Manuel Alija-Pérez, Maria-Esther Vidal +2
Background: Eating disorders are increasingly prevalent, and social networks offer valuable information. Objective: Our goal was to identify efficient machine learning models for c…
Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts
José Alberto Benítez-Andrades, María Teresa García-Ordás, Mayra Russo +3
Social networks are vital for information sharing, especially in the health sector for discussing diseases and treatments. These platforms, however, often feature posts as brief te…
Heart disease risk prediction using deep learning techniques with feature augmentation
María Teresa García-Ordás, Martín Bayón-Gutiérrez, Carmen Benavides +2
Cardiovascular diseases state as one of the greatest risks of death for the general population. Late detection in heart diseases highly conditions the chances of survival for patie…
Determining the severity of Parkinson's disease in patients using a multi task neural network
María Teresa García-Ordás, José Alberto Benítez-Andrades, Jose Aveleira-Mata +2
Parkinson's disease is easy to diagnose when it is advanced, but it is very difficult to diagnose in its early stages. Early diagnosis is essential to be able to treat the symptoms…
Multispecies bird sound recognition using a fully convolutional neural network
María Teresa García-Ordás, Sergio Rubio-Martín, José Alberto Benítez-Andrades +2
This study proposes a method based on fully convolutional neural networks (FCNs) to identify migratory birds from their songs, with the objective of recognizing which birds pass th…
Combining shape and contour features to improve tool wear monitoring in milling processes
M. T. García-Ordás, E. Alegre-Gutiérrez, V. González-Castro +1
In this paper, a new system based on combinations of a shape descriptor and a contour descriptor has been proposed for classifying inserts in milling processes according to their w…
Tool wear monitoring using an online, automatic and low cost system based on local texture
M. T. García-Ordás, E. Alegre-Gutiérrez, R. Alaiz-Rodríguez +1
In this work we propose a new online, low cost and fast approach based on computer vision and machine learning to determine whether cutting tools used in edge profile milling proce…
A comparative study on feature selection for a risk prediction model for colorectal cancer
N. Cueto-López, M. T. García-Ordás, V. Dávila-Batista +3
Background and objective Risk prediction models aim at identifying people at higher risk of developing a target disease. Feature selection is particularly important to improve the…
A generalized decision tree ensemble based on the NeuralNetworks architecture: Distributed Gradient Boosting Forest (DGBF)
Ángel Delgado-Panadero, José Alberto Benítez-Andrades, María Teresa García-Ordás
Tree ensemble algorithms as RandomForest and GradientBoosting are currently the dominant methods for modeling discrete or tabular data, however, they are unable to perform a hierar…
Adolescent relational behaviour and the obesity pandemic: A descriptive study applying social network analysis and machine learning techniques
Pilar Marqués-Sánchez, María Cristina Martínez-Fernández, José Alberto Benítez-Andrades +3
Aim: To study the existence of subgroups by exploring the similarities between the attributes of the nodes of the groups, in relation to diet and gender and, to analyse the connect…
Survival and grade of the glioma prediction using transfer learning
Santiago Valbuena Rubio, María Teresa García-Ordás, Oscar García-Olalla Olivera +3
Glioblastoma is a highly malignant brain tumor with a life expectancy of only 3 to 6 months without treatment. Detecting and predicting its survival and grade accurately are crucia…
Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network
María Teresa García-Ordás, Héctor Alaiz-Moretón, José Alberto Benítez-Andrades +3
In this work, a sentiment analysis method that is capable of accepting audio of any length, without being fixed a priori, is proposed. Mel spectrogram and Mel Frequency Cepstral Co…
Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data
María Teresa García-Ordás, José Alberto Benítez-Andrades, Isaías García-Rodríguez +2
The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was used. Thi…