Giacomo Cappon

Giacomo Cappon

Assistant Professor @ DEI, University of Padova, YOLO committer

Top Publications

ReplayBG: A Digital Twin-Based Methodology to Identify a Personalized Model from Type 1 Diabetes Data and Simulate Glucose Concentrations to Assess Alternative Therapies

Published in IEEE Transactions on Biomedical Engineering, 2023

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Recommended citation: Cappon G, Vettoretti M, Sparacino G, Del Favero S, Facchinetti A. ReplayBG: A Digital Twin-Based Methodology to Identify a Personalized Model from Type 1 Diabetes Data and Simulate Glucose Concentrations to Assess Alternative Therapies. IEEE Trans Biomed Eng. 2023 Jun 27. doi: 10.1109/TBME.2023.3286856. Epub ahead of print. PMID: 37368794. http://gcappon.github.io/files/cappon_tbme_2023.pdf

Individualized Models for Glucose Prediction in Type 1 Diabetes: Comparing Black-box Approaches To a Physiological White-box One

Published in IEEE Transactions on Biomedical Engineering, 2023

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Recommended citation: Cappon G, Prendin F, Sparacino G, Facchinetti A, Del Favero S. Individualized Models for Glucose Prediction in Type 1 Diabetes: Comparing Black-box Approaches To a Physiological White-box One. IEEE Trans Biomed Eng. 2023 May 17. doi: 10.1109/TBME.2023.3276193. Epub ahead of print. PMID: 37195837. http://gcappon.github.io/files/cappon_prendin_tbme_2023.pdf

Methods for Insulin Bolus Adjustment Based on the Continuous Glucose Monitoring Trend Arrows in Type 1 Diabetes: Performance and Safety Assessment in an In Silico Clinical Trial

Published in Journal of Diabetes Science and Technology, 2021

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Recommended citation: Noaro G, Cappon G, Sparacino G, Boscari F, Bruttomesso D, Facchinetti A. Methods for Insulin Bolus Adjustment Based on the Continuous Glucose Monitoring Trend Arrows in Type 1 Diabetes: Performance and Safety Assessment in an In Silico Clinical Trial. J Diabetes Sci Technol. 2021 Sep 6:19322968211043162. doi: 10.1177/19322968211043162. Epub ahead of print. PMID: 34486426. http://gcappon.github.io/files/noaro_jdst_2021.pdf

An Integrated Mobile Platform for Automated Data Collection and Real-Time Patient Monitoring in Diabetes Clinical Trials

Published in Journal of Diabetes Science and Technology, 2021

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Recommended citation: Cappon G, Cossu L, Boscari F, Bruttomesso D, Sparacino G, Facchinetti A. An Integrated Mobile Platform for Automated Data Collection and Real-Time Patient Monitoring in Diabetes Clinical Trials. J Diabetes Sci Technol. 2021 Jul 3:19322968211024620. doi: 10.1177/19322968211024620. Epub ahead of print. PMID: 34218721. http://gcappon.github.io/files/cappon_jdst_2021.pdf

Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy

Published in IEEE Transactions on Biomedical Engineering, 2021

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Recommended citation: Noaro G, Cappon G, Vettoretti M, Sparacino G, Favero SD, Facchinetti A. Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy. IEEE Trans Biomed Eng. 2021 Jan;68(1):247-255. doi: 10.1109/TBME.2020.3004031. Epub 2020 Dec 21. PMID: 32746033. http://gcappon.github.io/files/noaro_tbme_2021.pdf

Predicting Quality of Overnight Glycaemic Control in Type 1 Diabetes Using Binary Classifiers

Published in IEEE Journal of Biomedical Informatics, 2019

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Recommended citation: Guemes A, Cappon G, Hernandez B, Reddy M, Oliver N, Georgiou P, Herrero P. Predicting Quality of Overnight Glycaemic Control in Type 1 Diabetes Using Binary Classifiers. IEEE J Biomed Health Inform. 2020 May;24(5):1439-1446. doi: 10.1109/JBHI.2019.2938305. Epub 2019 Sep 13. PMID: 31536025. http://gcappon.github.io/files/guemes_jbhi_2019.pdf

Classification of Postprandial Glycemic Status with Application to Insulin Dosing in Type 1 Diabetes-An In Silico Proof-of-Concept

Published in Sensors (Basel), 2019

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Recommended citation: Cappon G, Facchinetti A, Sparacino G, Georgiou P, Herrero P. Classification of Postprandial Glycemic Status with Application to Insulin Dosing in Type 1 Diabetes-An In Silico Proof-of-Concept. Sensors (Basel). 2019 Jul 18;19(14):3168. doi: 10.3390/s19143168. PMID: 31323886; PMCID: PMC6679291. http://gcappon.github.io/files/cappon_sensors_2019.pdf

Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications

Published in Diabetes & Metabolism Journal, 2019

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Recommended citation: Cappon G, Vettoretti M, Sparacino G, Facchinetti A. Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications. Diabetes Metab J. 2019 Aug;43(4):383-397. doi: 10.4093/dmj.2019.0121. PMID: 31441246; PMCID: PMC6712232. http://gcappon.github.io/files/cappon_dmj_2019.pdf

In Silico Assessment of Literature Insulin Bolus Calculation Methods Accounting for Glucose Rate of Change

Published in Journal of Diabetes Science and Technology, 2018

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Recommended citation: Cappon G, Marturano F, Vettoretti M, Facchinetti A, Sparacino G. In Silico Assessment of Literature Insulin Bolus Calculation Methods Accounting for Glucose Rate of Change. J Diabetes Sci Technol. 2019 Jan;13(1):103-110. doi: 10.1177/1932296818777524. Epub 2018 May 31. PMID: 29848104; PMCID: PMC6313276. http://gcappon.github.io/files/cappon_jdst_2018_2.pdf

A Neural-Network-Based Approach to Personalize Insulin Bolus Calculation Using Continuous Glucose Monitoring

Published in Journal of Diabetes Science and Technology, 2018

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Recommended citation: Cappon G, Vettoretti M, Marturano F, Facchinetti A, Sparacino G. A Neural-Network-Based Approach to Personalize Insulin Bolus Calculation Using Continuous Glucose Monitoring. J Diabetes Sci Technol. 2018 Mar;12(2):265-272. doi: 10.1177/1932296818759558. PMID: 29493356; PMCID: PMC5851237. http://gcappon.github.io/files/cappon_jdst_2018.pdf