activity
20202026
most citedCOVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray images

26 citations · 40 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2026

DISCERN: Distributional Synthetic Replay for Retain-Free Incremental Machine Unlearning

Nicolás Segura-Kunsagi, Juan Luis Suárez-Díaz, Iván Sevillano-García +1

Machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch. In real deployments, however, deletion requests arri…

cs.AI2025★ 5 cited

A three-Level Framework for LLM-Enhanced eXplainable AI: From technical explanations to natural language

Marilyn Bello, Rafael Bello, Maria-Matilde García +3

The growing application of artificial intelligence in sensitive domains has intensified the demand for systems that are not only accurate but also explainable and trustworthy. Alth…

cs.LG2025

STOOD-X methodology: using statistical nonparametric test for OOD Detection Large-Scale datasets enhanced with explainability

Iván Sevillano-García, Julián Luengo, Francisco Herrera

Out-of-Distribution (OOD) detection is a critical task in machine learning, particularly in safety-sensitive applications where model failures can have serious consequences. Howeve…

cs.AI2024

X-SHIELD: Regularization for eXplainable Artificial Intelligence

Iván Sevillano-García, Julián Luengo, Francisco Herrera

As artificial intelligence systems become integral across domains, the demand for explainability grows, the called eXplainable artificial intelligence (XAI). Existing efforts prima…

cs.AI2022★ 9 cited

REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study

Iván Sevillano-García, Julián Luengo-Martín, Francisco Herrera

Explainable artificial intelligence is proposed to provide explanations for reasoning performed by an Artificial Intelligence. There is no consensus on how to evaluate the quality…

eess.IV2020★ 26 cited

COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray images

S. Tabik, A. Gómez-Ríos, J. L. Martín-Rodríguez +10

Currently, Coronavirus disease (COVID-19), one of the most infectious diseases in the 21st century, is diagnosed using RT-PCR testing, CT scans and/or Chest X-Ray (CXR) images. CT…