Prediction of ICU admission for COVID-19 patients: a Machine Learning approach based on Complete Blood Count data. - Lorenzo Famiglini; Giorgio Bini; Anna Carobene; Andrea Campagner; Federico Cabitza (CBMS, 2021)

The importance of being external. methodological insights for the external validation of machine learning models in medicine. - Federico Cabitza; Andrea Campagner; Felipe Soares; Luis García de Guadiana-Romualdo; Feyissa Challa; Adela Sulejmani; Michela Seghezzi; Anna Carobene (Comput. Methods Programs Biomed., 2021)

External validation of Machine Learning models for COVID-19 detection based on Complete Blood Count. - Andrea Campagner; Anna Carobene; Federico Cabitza (Health Inf. Sci. Syst., 2021)

Everything is Varied: The Surprising Impact of Individual Variation on ML Robustness in Medicine. - Andrea Campagner; Lorenzo Famiglini; Anna Carobene; Federico Cabitza (CoRR, 2022)

Everything is varied: The surprising impact of instantial variation on ML reliability. - Andrea Campagner; Lorenzo Famiglini; Anna Carobene; Federico Cabitza (Appl. Soft Comput., 2023)