Type 1 diabetes and Artificial pancreas are two areas of study in which Giovanni Sparacino engages in interdisciplinary research. Giovanni Sparacino carries out multidisciplinary research, doing studies in Artificial pancreas and Type 1 diabetes. His research on Diabetes mellitus often connects related areas such as Continuous glucose monitoring. His research is interdisciplinary, bridging the disciplines of Diabetes mellitus and Continuous glucose monitoring. His Endocrinology study frequently draws parallels with other fields, such as Insulin delivery. Giovanni Sparacino combines topics linked to Endocrinology with his work on Insulin delivery. He conducts interdisciplinary study in the fields of Statistics and Time series through his works. In his work, Giovanni Sparacino performs multidisciplinary research in Time series and Autoregressive model. In his works, he performs multidisciplinary study on Autoregressive model and Statistics.
His research investigates the link between Series (stratigraphy) and topics such as Paleontology that cross with problems in Context (archaeology). His Context (archaeology) study frequently intersects with other fields, such as Paleontology. While the research belongs to areas of Channel (broadcasting), he spends his time largely on the problem of Telecommunications, intersecting his research to questions surrounding Signal-to-noise ratio (imaging). His research links Telecommunications with Signal-to-noise ratio (imaging). He links relevant research areas such as Jump and Impulse (physics) in the realm of Quantum mechanics. His Impulse (physics) study often links to related topics such as Quantum mechanics. Artificial intelligence and False positive paradox are frequently intertwined in his study. His study on Endocrinology is mostly dedicated to connecting different topics, such as Glycemic. His Glycemic study frequently draws connections between adjacent fields such as Blood Glucose Self-Monitoring.
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Diabetes: Models, Signals, and Control
C. Cobelli;C. Dalla Man;G. Sparacino;L. Magni.
IEEE Reviews in Biomedical Engineering (2009)
Glucose Concentration can be Predicted Ahead in Time From Continuous Glucose Monitoring Sensor Time-Series
G. Sparacino;F. Zanderigo;S. Corazza;A. Maran.
IEEE Transactions on Biomedical Engineering (2007)
Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring.
C Pérez-Gandía;A Facchinetti;G Sparacino;C Cobelli.
Diabetes Technology & Therapeutics (2010)
Nonparametric input estimation in physiological systems: problems, methods, and case studies
Giuseppe de Nicolao;Giovanni Sparacino;Claudio Cobelli.
Wearable Continuous Glucose Monitoring Sensors: A Revolution in Diabetes Treatment
Giacomo Cappon;Giada Acciaroli;Martina Vettoretti;Andrea Facchinetti.
Neural Network Incorporating Meal Information Improves Accuracy of Short-Time Prediction of Glucose Concentration
C. Zecchin;A. Facchinetti;G. Sparacino;G. De Nicolao.
IEEE Transactions on Biomedical Engineering (2012)
Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications
Giacomo Cappon;Martina Vettoretti;Giovanni Sparacino;Andrea Facchinetti.
Diabetes & Metabolism Journal (2019)
Modeling the Glucose Sensor Error
Andrea Facchinetti;Simone Del Favero;Giovanni Sparacino;Jessica R. Castle.
IEEE Transactions on Biomedical Engineering (2014)
Real-Time Improvement of Continuous Glucose Monitoring Accuracy: The smart sensor concept
Andrea Facchinetti;Giovanni Sparacino;Stefania Guerra;Yoeri M. Luijf.
Diabetes Care (2013)
"Smart" Continuous Glucose Monitoring Sensors: On-Line Signal Processing Issues
Giovanni Sparacino;Andrea Facchinetti;Claudio Cobelli.
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