132 citations · 867 across the 32 of their papers we have counts for
32 papers
Predicting fall risk in older adults: A machine learning comparison of accelerometric and non-accelerometric factors
Ana González-Castro, José Alberto Benítez-Andrades, Rubén González-González +2
This study investigates fall risk prediction in older adults using various machine learning models trained on accelerometric, non-accelerometric, and combined data from 146 partici…
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…
Enhanced prediction of spine surgery outcomes using advanced machine learning techniques and oversampling methods
José Alberto Benítez-Andrades, Camino Prada-García, Nicolás Ordás-Reyes +3
The study proposes an advanced machine learning approach to predict spine surgery outcomes by incorporating oversampling techniques and grid search optimization. A variety of model…
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…
Application of Machine Learning Algorithms in Classifying Postoperative Success in Metabolic Bariatric Surgery: A Comprehensive Study
José Alberto Benítez-Andrades, Camino Prada-García, Rubén García-Fernández +3
Objectives: Metabolic Bariatric Surgery (MBS) is a critical intervention for patients living with obesity and related health issues. Accurate classification and prediction of patie…
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…
A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies
José Alberto Benítez-Andrades, Alejandro Rodríguez-González, Carmen Benavides +2
Social Network Analysis (SNA) is a set of techniques developed in the field of social and behavioral sciences research, in order to characterize and study the social relationships…
Thermal Infrared Imaging to Evaluate Emotional Competences in Nursing Students: A First Approach through a Case Study
Pilar Marqués-Sánchez, Cristina Liébana-Presa, José Alberto Benítez-Andrades +3
During nursing studies, it is crucial to develop emotional skills for both academic success and quality patient care. Utilizing technologies like thermography can be instrumental i…
Social network analysis for personalized characterization and risk assessment of alcohol use disorders in adolescents using semantic technologies
José Alberto Benítez-Andrades, Isaías García-Rodríguez, Carmen Benavides +2
Alcohol Use Disorder (AUD) is a major concern for public health organizations worldwide, especially as regards the adolescent population. The consumption of alcohol in adolescents…
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…
The socialisation of the adolescent who carries out team sports: a transversal study of centrality with a social network analysis
Pilar Marqués-Sánchez, José Alberto Benítez-Andrades, María Dolores Calvo Sánchez +1
Objectives: This study analyzed adolescent physical activity, its link to overweight, and the social network structure in group sports participants, focusing on centrality measures…
A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence
José Alberto Benítez-Andrades, Tania Fernández-Villa, Carmen Benavides +3
The COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human beha…
Identification of cohesive subgroups in a university hall of residence during the COVID-19 pandemic using a social network analysis approach
Pilar Marqués-Sánchez, Arrate Pinto-Carral, Tania Fernández-Villa +3
The aims: (i) analyze connectivity between subgroups of university students, (ii) assess which bridges of relational contacts are essential for connecting or disconnecting subgroup…
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…