Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset. - Carlos Sáez; Nekane Romero; J. Alberto Conejero; Juan M. García-Gómez (J. Am. Medical Informatics Assoc., 2021)

Extremely missing numerical data in Electronic Health Records for machine learning can be managed through simple imputation methods considering informative missingness: A comparative of solutions in a COVID-19 mortality case study. - Pablo Ferri Borreda; Nekane Romero-Garcia; Rafael Badenes; David Lora-Pablos; Teresa García Morales; Agustín Gómez De La Camara; Juan M. García-Gómez; Carlos Sáez (Comput. Methods Programs Biomed., 2023)