45 citations · 147 across the 11 of their papers we have counts for
11 papers
Automated ICD Classification of Psychiatric Diagnoses: From Classical NLP to Large Language Models
Fernando Ortega, Raúl Lara-Cabrera, Jorge Dueñas-Lerín +3
Mental health has become a global priority, leading to a massive administrative burden in the coding of clinical diagnoses. This study proposes the automation of psychiatric diagno…
Efficient n-body simulations using physics informed graph neural networks
Víctor Ramos-Osuna, Alberto Díaz-Álvarez, Raúl Lara-Cabrera
This paper presents a novel approach for accelerating n-body simulations by integrating a physics-informed graph neural networks (GNN) with traditional numerical methods. Our metho…
Statistical Analysis of Risk Assessment Factors and Metrics to Evaluate Radicalisation in Twitter
Raul Lara-Cabrera, Antonio Gonzalez-Pardo, David Camacho
Nowadays, Social Networks have become an essential communication tools producing a large amount of information about their users and their interactions, which can be analysed with…
Deep Neural Aggregation for Recommending Items to Group of Users
Jorge Dueñas-Lerín, Raúl Lara-Cabrera, Fernando Ortega +1
Modern society devotes a significant amount of time to digital interaction. Many of our daily actions are carried out through digital means. This has led to the emergence of numero…
An evaluation framework for dimensionality reduction through sectional curvature
Raúl Lara-Cabrera, Ángel González-Prieto, Diego Pérez-López +2
Unsupervised machine learning lacks ground truth by definition. This poses a major difficulty when designing metrics to evaluate the performance of such algorithms. In sharp contra…
Neural Group Recommendation Based on a Probabilistic Semantic Aggregation
Jorge Dueñas-Lerín, Raúl Lara-Cabrera, Fernando Ortega +1
Recommendation to groups of users is a challenging subfield of recommendation systems. Its key concept is how and where to make the aggregation of each set of user information into…
Using 3D printed badges to improve student performance and reduce dropout rates in STEM higher education
Raúl Lara-Cabrera, Fernando Ortega, Edgar Talavera +1
Students' perception of excessive difficulty in STEM degrees lowers their motivation and therefore affects their performance. According to prior research, the use of gamification t…
Restricted Bernoulli Matrix Factorization: Balancing the trade-off between prediction accuracy and coverage in classification based collaborative filtering
Ángel González-Prieto, Abraham Gutiérrez, Fernando Ortega +1
Reliability measures associated with the prediction of the machine learning models are critical to strengthening user confidence in artificial intelligence. Therefore, those models…
Deep Learning feature selection to unhide demographic recommender systems factors
Jesús Bobadilla, Ángel González-Prieto, Fernando Ortega +1
Extracting demographic features from hidden factors is an innovative concept that provides multiple and relevant applications. The matrix factorization model generates factors whic…
DeepFair: Deep Learning for Improving Fairness in Recommender Systems
Jesús Bobadilla, Raúl Lara-Cabrera, Ángel González-Prieto +1
The lack of bias management in Recommender Systems leads to minority groups receiving unfair recommendations. Moreover, the trade-off between equity and precision makes it difficul…
Providing reliability in Recommender Systems through Bernoulli Matrix Factorization
Fernando Ortega, Raúl Lara-Cabrera, Ángel González-Prieto +1
Beyond accuracy, quality measures are gaining importance in modern recommender systems, with reliability being one of the most important indicators in the context of collaborative…