Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases. - Michela Carlotta Massi; Francesca Ieva; Emanuele Lettieri (BMC Medical Informatics Decis. Mak., 2020)

Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification. - Michela Carlotta Massi; Francesca Ieva (MLSP, 2021)

Learning High-Order Interactions via Targeted Pattern Search. - Michela Carlotta Massi; Nicola R. Franco; Francesca Ieva; Andrea Manzoni; Anna Maria Paganoni; Paolo Zunino (CoRR, 2021)

A Deep Variational Approach to Clustering Survival Data. - Laura Manduchi; Ricards Marcinkevics; Michela Carlotta Massi; Verena Gotta; Timothy Müller; Flavio Vasella; Marian C. Neidert; Marc Pfister; Julia E. Vogt (CoRR, 2021)

A Deep Variational Approach to Clustering Survival Data. - Laura Manduchi; Ricards Marcinkevics; Michela Carlotta Massi; Thomas J. Weikert; Alexander Sauter; Verena Gotta; Timothy Müller; Flavio Vasella; Marian C. Neidert; Marc Pfister; Bram Stieltjes; Julia E. Vogt (ICLR, 2022)

Feature selection for imbalanced data with deep sparse autoencoders ensemble. - Michela Carlotta Massi; Francesca Gasperoni; Francesca Ieva; Anna Maria Paganoni (Stat. Anal. Data Min., 2022)

A Deep Survival EWAS approach estimating risk profile based on pre-diagnostic DNA methylation: An application to breast cancer time to diagnosis. - Michela Carlotta Massi; Lorenzo Dominoni; Francesca Ieva; Giovanni Fiorito (PLoS Comput. Biol., 2022)