| Continuous glucose monitoring sensors for diabetes management: a review of technologies and applications G Cappon, M Vettoretti, G Sparacino, A Facchinetti Diabetes & metabolism journal 43 (4), 383-397, 2019 | 371 | 2019 |
| Wearable continuous glucose monitoring sensors: a revolution in diabetes treatment G Cappon, G Acciaroli, M Vettoretti, A Facchinetti, G Sparacino Electronics 6 (3), 65, 2017 | 249 | 2017 |
| 2019 Clinical practice guidelines for type 2 diabetes mellitus in Korea G Cappon, M Vettoretti, G Sparacino, A Facchinetti, MK Kim, SH Ko, ... Diabetes & metabolism journal 43 (4), 398-406, 2019 | 220 | 2019 |
| Advanced diabetes management using artificial intelligence and continuous glucose monitoring sensors M Vettoretti, G Cappon, A Facchinetti, G Sparacino Sensors 20 (14), 3870, 2020 | 108 | 2020 |
| Continuous glucose monitoring: current use in diabetes management and possible future applications M Vettoretti, G Cappon, G Acciaroli, A Facchinetti, G Sparacino Journal of diabetes science and technology 12 (5), 1064-1071, 2018 | 87 | 2018 |
| A neural-network-based approach to personalize insulin bolus calculation using continuous glucose monitoring G Cappon, M Vettoretti, F Marturano, A Facchinetti, G Sparacino Journal of diabetes science and technology 12 (2), 265-272, 2018 | 75 | 2018 |
| Predicting quality of overnight glycaemic control in type 1 diabetes using binary classifiers A Güemes, G Cappon, B Hernandez, M Reddy, N Oliver, P Georgiou, ... IEEE journal of biomedical and health informatics 24 (5), 1439-1446, 2019 | 53 | 2019 |
| Machine-learning based model to improve insulin bolus calculation in type 1 diabetes therapy G Noaro, G Cappon, M Vettoretti, G Sparacino, S Del Favero, ... IEEE Transactions on Biomedical Engineering 68 (1), 247-255, 2020 | 52 | 2020 |
| Heterogeneity and nearest-neighbor coupling can explain small-worldness and wave properties in pancreatic islets G Cappon, MG Pedersen Chaos: An Interdisciplinary Journal of Nonlinear Science 26 (5), 2016 | 41 | 2016 |
| The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using SHAP F Prendin, J Pavan, G Cappon, S Del Favero, G Sparacino, A Facchinetti Scientific reports 13 (1), 16865, 2023 | 31 | 2023 |
| Classification of postprandial glycemic status with application to insulin dosing in type 1 diabetes—An in silico proof-of-concept G Cappon, A Facchinetti, G Sparacino, P Georgiou, P Herrero Sensors 19 (14), 3168, 2019 | 30 | 2019 |
| A real-time continuous glucose monitoring–based algorithm to trigger hypotreatments to prevent/mitigate hypoglycemic events N Camerlingo, M Vettoretti, S Del Favero, G Cappon, G Sparacino, ... Diabetes Technology & Therapeutics 21 (11), 644-655, 2019 | 24 | 2019 |
| ReplayBG: a digital twin-based methodology to identify a personalized model from type 1 diabetes data and simulate glucose concentrations to assess alternative therapies G Cappon, M Vettoretti, G Sparacino, S Del Favero, A Facchinetti IEEE Transactions on Biomedical Engineering 70 (11), 3227-3238, 2023 | 19 | 2023 |
| A Personalized and Interpretable Deep Learning Based Approach to Predict Blood Glucose Concentration in Type 1 Diabetes. G Cappon, L Meneghetti, F Prendin, J Pavan, G Sparacino, S Del Favero, ... KDH@ ECAI 20, 75-79, 2020 | 19 | 2020 |
| In silico assessment of literature insulin bolus calculation methods accounting for glucose rate of change G Cappon, F Marturano, M Vettoretti, A Facchinetti, G Sparacino Journal of diabetes science and technology 13 (1), 103-110, 2019 | 19 | 2019 |
| A personalized and adaptive insulin bolus calculator based on double deep q-learning to improve type 1 diabetes management G Noaro, T Zhu, G Cappon, A Facchinetti, P Georgiou IEEE Journal of Biomedical and Health Informatics 27 (5), 2536-2544, 2023 | 12 | 2023 |
| Digital solutions to diagnose and manage postbariatric hypoglycemia KA Schönenberger, L Cossu, F Prendin, G Cappon, J Wu, KL Fuchs, ... Frontiers in Nutrition 9, 855223, 2022 | 12 | 2022 |
| Personalized Machine Learning Algorithm based on Shallow Network and Error Imputation Module for an Improved Blood Glucose Prediction. J Pavan, F Prendin, L Meneghetti, G Cappon, G Sparacino, A Facchinetti, ... KDH@ ECAI, 95-99, 2020 | 12 | 2020 |
| Individualized models for glucose prediction in type 1 diabetes: comparing black-box approaches to a physiological white-box one G Cappon, F Prendin, A Facchinetti, G Sparacino, S Del Favero IEEE Transactions on Biomedical Engineering 70 (11), 3105-3115, 2023 | 11 | 2023 |
| An integrated mobile platform for automated data collection and real-time patient monitoring in diabetes clinical trials G Cappon, L Cossu, F Boscari, D Bruttomesso, G Sparacino, A Facchinetti Journal of Diabetes Science and Technology 16 (6), 1555-1559, 2022 | 11 | 2022 |
Andrea FacchinettiAssociate Professor, Department of Information Engineering, University of PadovaEmail verificata su dei.unipd.it
