Predicting Ovarian Cancer with Machine Learning: Integrating Clinical and Genetic Data. - Ismael Gómez-Talal; Arantzazu Barquín; Luis Bote-Curiel; Mónica Yagüe-Fernández; José Luis Rojo-Álvarez; Jesús García-Donas (EUSIPCO, 2023)

Understanding the disparities in Mathematics performance: An interpretability-based examination. - Ismael Gómez-Talal; Luis Bote-Curiel; José Luis Rojo-Álvarez (Eng. Appl. Artif. Intell., 2024)

Machine Learning in Hospitality: Interpretable Forecasting of Booking Cancellations. - Ismael Gómez-Talal; Mana Azizsoltani; Pilar Talón-Ballestero; Ashok Singh (IEEE Access, 2025)

Interpretable Machine Learning Models for PISA Results in Mathematics. - Ismael Gómez-Talal; Luis Bote-Curiel; José Luis Rojo-Álvarez (IEEE Access, 2025)

Towards Explainable Artificial Intelligence in Machine Learning: A study on efficient Perturbation-Based Explanations. - Ismael Gómez-Talal; Mana Azizsoltani; Luis Bote-Curiel; José Luis Rojo-Álvarez; Ashok Singh (Eng. Appl. Artif. Intell., 2025)

Corrigendum to "Understanding the disparities in Mathematics performance: An interpretability-based examination" [Eng. Appl. Artif. Intell. 133 Part B (2024) 108109]. - Ismael Gómez-Talal; Luis Bote-Curiel; José Luis Rojo-Álvarez (Eng. Appl. Artif. Intell., 2025)