Early Experience in Forecasting Blood Glucose Levels Using a Delayed and Auto-Regressive Jump Neural Network. - Federico D'Antoni; Mario Merone; Vincenzo Piemonte; Paolo Pozzilli; Giulio Iannello; Paolo Soda (ICCI*CC, 2019)

Auto-Regressive Time Delayed jump neural network for blood glucose levels forecasting. - Federico D'Antoni; Mario Merone; Vincenzo Piemonte; Giulio Iannello; Paolo Soda (Knowl. Based Syst., 2020)

Exploiting AI to make insulin pens smart: injection site recognition and lipodystrophy detection. - Elisabetta Torre; Luisa Francini; Ermanno Cordelli; Rosa Sicilia; Silvia Manfrini; Vincenzo Piemonte; Paolo Soda (CBMS, 2022)

Layered Meta-Learning Algorithm for Predicting Adverse Events in Type 1 Diabetes. - Federico D'Antoni; Lorenzo Petrosino; Alessandro Marchetti; Luca Bacco; Silvia Pieralice; Luca Vollero; Paolo Pozzilli; Vincenzo Piemonte; Mario Merone (IEEE Access, 2023)

A New Glycemic closed-loop control based on Dyna-Q for Type-1-Diabetes. - Silvia Del Giorno; Federico D'Antoni; Vincenzo Piemonte; Mario Merone (Biomed. Signal Process. Control., 2023)

AI-Powered Insulin Pens for Pediatric Diabetes: Advancements in Lipodystrophy Detection and Injection Site Recognition. - Lorenzo Pede; Mariangela Martino; Maria Elisa Amodeo; Francesca Silvestri; Sebastiano Battista Romano Viglialoro; Daria Maggi; Dario Tuccinardi; Vincenzo Piemonte; Silvia Manfrini; Riccardo Schiaffini; Paolo Soda; Ermanno Cordelli (CBMS, 2025)