Interpretable Data-Driven Approach Based on Feature Selection Methods and GAN-Based Models for Cardiovascular Risk Prediction in Diabetic Patients. - David Chushig-Muzo; Hugo Calero-Díaz; Francisco J. Lara-Abelenda; Vanesa Gómez-Martínez; Conceição Granja; Cristina Soguero-Ruíz (IEEE Access, 2024)

LM-IGTD: a 2D image generator for low-dimensional and mixed-type tabular data to leverage the potential of convolutional neural networks. - Vanesa Gómez-Martínez; Francisco J. Lara-Abelenda; Pablo Peiro-Corbacho; David Chushig-Muzo; Conceição Granja; Cristina Soguero-Ruíz (CoRR, 2024)

Navigating the Digital Neurolandscape: Analyzing the Social Perception of and Sentiments Regarding Neurological Disorders through Topic Modeling and Unsupervised Research Using Twitter. - Javier Domingo-Espiñeira; Oscar Fraile-Martínez; Cielo Garcia-Montero; María Montero; Andrea Varaona; Francisco J. Lara-Abelenda; Miguel A. Ortega; Melchor Alvarez-Mon; Miguel Angel Alvarez-Mon (Inf., 2024)

Personalized glucose forecasting for people with type 1 diabetes using large language models. - Francisco J. Lara-Abelenda; David Chushig-Muzo; Pablo Peiro-Corbacho; Ana M. Wägner; Conceição Granja; Cristina Soguero-Ruíz (Comput. Methods Programs Biomed., 2025)

Interpretable and multimodal fusion methodology to predict severe hypoglycemia in adults with type 1 diabetes. - Francisco J. Lara-Abelenda; David Chushig-Muzo; Ana M. Wägner; Maryam Tayefi; Cristina Soguero-Ruíz (Eng. Appl. Artif. Intell., 2025)

Transfer learning for a tabular-to-image approach: A case study for cardiovascular disease prediction. - Francisco J. Lara-Abelenda; David Chushig-Muzo; Pablo Peiro-Corbacho; Vanesa Gómez-Martínez; Ana M. Wägner; Conceição Granja; Cristina Soguero-Ruíz (J. Biomed. Informatics, 2025)