We develop methodological tools, algorithms and software to analyze data and vital signals reflecting individual health and to exploit them with learning techniques to improve patient therapy, possibly creating real-time feedback mechanisms. Tools are personalized, adaptive, proactive and equipped with intelligent self-diagnostic functions. Models to predict and prevent the incidence of new diseases or medical complications are also investigated. Our main clinical application is the treatment of diabetes mellitus, but we are also involved in projects aimed at predicting the onset of cardiovascular and chronic respiratory diseases and in cognitive neuroscience investigations.
Group members
Giovanni Sparacino, Full professor
Andrea Facchinetti, Associate professor
Simone Del Favero, Assistant professor
Martina Vettoretti, Assistant Professor
Giacomo Cappon, Junior post-doc research fellow
Enrico Longato, Junior post-doc research fellow
Simone Faccioli, PhD student
Nunzio Camerlingo, PhD student
Giulia Noaro, PhD student
Jacopo Pavan, PhD student
Francesco Prendin, PhD student
Chiara Roversi, PhD student
Alessandro Guazzo, PhD student
Eleonora Manzoni, PhD student
Luca Cossu, Research collaborator
Former group members
Maria Rubega (PhD awarded in 2017)
Giada Acciaroli (PhD awarded in 2019)
Francesca Marturano (PhD awarded in 2021)
Lorenzo Meneghetti (PhD awarded in 2021)