132 citations · 867 across the 32 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…
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…
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…