no code implementations • 29 Mar 2024 • José Alberto Benítez-Andrades, Camino Prada-García, Rubén García-Fernández, María D. Ballesteros-Pomar, María-Inmaculada González-Alonso, Antonio Serrano-García
This study presents a novel machine learning approach to classify patients in the context of metabolic bariatric surgery, providing insights into the efficacy of different models and variable types.
no code implementations • 6 Mar 2024 • Sergio Rubio-Martín, María Teresa García-Ordás, Martín Bayón-Gutiérrez, Natalia Prieto-Fernández, José Alberto Benítez-Andrades
Purpose: Our study explored the use of artificial intelligence (AI) to diagnose autism spectrum disorder (ASD).
no code implementations • 19 Feb 2024 • María Teresa García-Ordás, Natalia Arias, Carmen Benavides, Oscar García-Olalla, José Alberto Benítez-Andrades
COVID-19 disease has affected almost every country in the world.
no code implementations • 14 Feb 2024 • José Alberto Benítez-Andrades, José Emilio Labra, Enedina Quiroga, Vicente Martín, Isaías García, Pilar Marqués-Sánchez, Carmen Benavides
There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people.
no code implementations • 14 Feb 2024 • José Alberto Benítez-Andrades, María Teresa García-Ordás, María Álvarez-González, Raquel Leirós-Rodríguez, Ana F López Rodríguez
Objective: The study aims to evaluate the most influential variables in PUI using machine learning, focusing on intrinsic, extrinsic, and combined variable groups.
no code implementations • 14 Feb 2024 • José Alberto Benítez-Andrades, Alejandro Rodríguez-González, Carmen Benavides, Leticia Sánchez-Valdeón, Isaías García
When building a social network for performing an SNA analysis, an initial process of data gathering is achieved in order to extract the characteristics of the individuals and their relationships.
no code implementations • 14 Feb 2024 • José Alberto Benítez-Andrades, Natalia Arias, María Teresa García-Ordás, Marta Martínez-Martínez, Isaías García-Rodríguez
The intervention group had access to the web through a user account and a password.
no code implementations • 14 Feb 2024 • Ángel Delgado-Panadero, Beatriz Hernández-Lorca, María Teresa García-Ordás, José Alberto Benítez-Andrades
The proposed method takes advantage of the GBDT architecture to calculate the contribution of each feature using the residue of each node.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI)
no code implementations • 10 Feb 2024 • María Teresa García-Ordás, Héctor Alaiz-Moretón, José-Luis Casteleiro-Roca, Esteban Jove, José Alberto Benítez-Andrades, Isaías García-Rodríguez, Héctor Quintián, José Luis Calvo-Rolle
This work addresses the performance comparison between four clustering techniques with the objective of achieving strong hybrid models in supervised learning tasks.
no code implementations • 8 Feb 2024 • María Teresa García-Ordás, José Alberto Benítez-Andrades, Jose Aveleira-Mata, José-Manuel Alija-Pérez, Carmen Benavides
Parkinson's disease is easy to diagnose when it is advanced, but it is very difficult to diagnose in its early stages.
no code implementations • 8 Feb 2024 • José Alberto Benítez-Andrades, José-Manuel Alija-Pérez, Maria-Esther Vidal, Rafael Pastor-Vargas, María Teresa García-Ordás
Background: Eating disorders are increasingly prevalent, and social networks offer valuable information.
no code implementations • 8 Feb 2024 • José Alberto Benítez-Andrades, María Teresa García-Ordás, Mayra Russo, Ahmad Sakor, Luis Daniel Fernandes Rotger, Maria-Esther Vidal
We tested our approach on a dataset of 2, 000 tweets about eating disorders, finding that merging word embeddings with knowledge graph information enhances the predictive models' reliability.
no code implementations • 8 Feb 2024 • María Teresa García-Ordás, Martín Bayón-Gutiérrez, Carmen Benavides, Jose Aveleira-Mata, José Alberto Benítez-Andrades
Cardiovascular diseases state as one of the greatest risks of death for the general population.
no code implementations • 4 Feb 2024 • 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 hierarchical representation learning from raw data as NeuralNetworks does thanks to its multi-layered structure, which is a key feature for DeepLearning problems and modeling unstructured data.
no code implementations • 4 Feb 2024 • Santiago Valbuena Rubio, María Teresa García-Ordás, Oscar García-Olalla Olivera, Héctor Alaiz-Moretón, Maria-Inmaculada González-Alonso, José Alberto Benítez-Andrades
In conclusion, this study presents a promising method for predicting the survival and grade of glioblastoma.
no code implementations • 4 Feb 2024 • Pilar Marqués-Sánchez, María Cristina Martínez-Fernández, José Alberto Benítez-Andrades, Enedina Quiroga-Sánchez, María Teresa García-Ordás, Natalia Arias-Ramos
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 connectivity between groups based on aspects of similarities between them through SNA and artificial intelligence techniques.
no code implementations • 3 Feb 2024 • María Teresa García-Ordás, Carmen Benavides, José Alberto Benítez-Andrades, Héctor Alaiz-Moretón, Isaías García-Rodríguez
Conclusions: Using a full deep learning pipeline for data preprocessing and classification has demonstrate to be very promising in the diabetes detection field outperforming the state-of-the-art proposals.
no code implementations • 3 Feb 2024 • María Teresa García-Ordás, Héctor Alaiz-Moretón, José Alberto Benítez-Andrades, Isaías García-Rodríguez, Oscar García-Olalla, Carmen Benavides
In this work, a sentiment analysis method that is capable of accepting audio of any length, without being fixed a priori, is proposed.
no code implementations • 3 Feb 2024 • José Alberto Benítez-Andrades, Isaías García-Rodríguez, Carmen Benavides, Héctor Aláiz-Moretón, José Emilio Labra Gayo
The complete procedure for carrying out a social network analysis (SNA) is a time-consuming task that entails a series of steps in which the expert in social network analysis could make mistakes.
no code implementations • 3 Feb 2024 • María Teresa García-Ordás, José Alberto Benítez-Andrades, Isaías García-Rodríguez, Carmen Benavides, Héctor Alaiz-Moretón
This dataset is composed of 920 sounds of which 810 are of chronic diseases, 75 of non-chronic diseases and only 35 of healthy individuals.