activity
20192024
most citedRandom Forest-Based Prediction of Stroke Outcome

135 citations · 166 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Segmentation, Classification and Interpretation of Breast Cancer Medical Images using Human-in-the-Loop Machine Learning

David Vázquez-Lema, Eduardo Mosqueira-Rey, Elena Hernández-Pereira +3

This paper explores the application of Human-in-the-Loop (HITL) strategies in training machine learning models in the medical domain. In this case a doctor-in-the-loop approach is…

cs.LG2024★ 135 cited

Random Forest-Based Prediction of Stroke Outcome

Carlos Fernandez-Lozano, Pablo Hervella, Virginia Mato-Abad +9

We research into the clinical, biochemical and neuroimaging factors associated with the outcome of stroke patients to generate a predictive model using machine learning techniques…

cs.LG2021

Ensemble of Convolution Neural Networks on Heterogeneous Signals for Sleep Stage Scoring

Enrique Fernandez-Blanco, Carlos Fernandez-Lozano, Alejandro Pazos +1

Over the years, several approaches have tried to tackle the problem of performing an automatic scoring of the sleeping stages. Although any polysomnography usually collects over a…

q-bio.QM2019★ 28 cited

Classification of signaling proteins based on molecular star graph descriptors using Machine Learning models

Carlos Fernandez-Lozano, Ruben F. Cuinas, Jose A. Seoane +3

Signaling proteins are an important topic in drug development due to the increased importance of finding fast, accurate and cheap methods to evaluate new molecular targets involved…

cs.LG2019★ 3 cited

A Hybrid Evolutionary System for Automated Artificial Neural Networks Generation and Simplification in Biomedical Applications

Enrique Fernandez-Blanco, Daniel Rivero, Marcos Gestal +4

Data mining and data classification over biomedical data are two of the most important research fields in computer science. Among the great diversity of techniques that can be used…