Global parenchymal texture features based on histograms of oriented gradients improve cancer development risk estimation from healthy breasts. - Francisco Javier Pérez-Benito; François Signol; Juan-Carlos Perez-Cortes; Marina Pollán; Beatriz Pérez-Gómez; Dolores Salas-Trejo; María Casals; Inmaculada Martínez; Rafael Llobet (Comput. Methods Programs Biomed., 2019)

A happiness degree predictor using the conceptual data structure for deep learning architectures. - Francisco Javier Pérez-Benito; Patricia Villacampa-Fernández; J. Alberto Conejero; Juan M. García-Gómez; Esperanza Navarro-Pardo (Comput. Methods Programs Biomed., 2019)

A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation. - Francisco Javier Pérez-Benito; François Signol; Juan-Carlos Perez-Cortes; Alejandro Fuster Baggetro; Marina Pollán; Beatriz Pérez-Gómez; Dolores Salas-Trejo; María Casals; Inmaculada Martínez; Rafael Llobet (Comput. Methods Programs Biomed., 2020)

Bias Analysis on Public X-Ray Image Datasets of Pneumonia and COVID-19 Patients. - Omar del Tejo Catalá; Ismael Salvador Igual; Francisco Javier Pérez-Benito; David Millán Escrivá; Vicent Ortiz Castelló; Rafael Llobet; Juan-Carlos Perez-Cortes (IEEE Access, 2021)

Extended a Priori Probability (EAPP): A Data-Driven Approach for Machine Learning Binary Classification Tasks. - Vicent Ortiz Castelló; Francisco Javier Pérez-Benito; Omar del Tejo Catalá; Ismael Salvador Igual; Rafael Llobet; Juan-Carlos Perez-Cortes (IEEE Access, 2022)

A deep learning framework to classify breast density with noisy labels regularization. - Hector Lopez-Almazan; Francisco Javier Pérez-Benito; Andrés Larroza; Juan-Carlos Perez-Cortes; Marina Pollán; Beatriz Pérez-Gómez; Dolores Salas-Trejo; María Casals; Rafael Llobet (Comput. Methods Programs Biomed., 2022)