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Andrea Facchinetti
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2020 – today
- 2024
- [j46]Chiara Roversi
, Nunzio Camerlingo
, Martina Vettoretti, Andrea Facchinetti
, Pratik Choudhary
, Giovanni Sparacino
, Simone Del Favero
:
Risk of hypoglycemia in type 1 diabetes management: An in-silico sensitivity analysis to assess and rank the quantitative impact of different behavioral factors. Comput. Methods Programs Biomed. 244: 107943 (2024) - [j45]Jacopo Pavan
, Giulia Noaro, Andrea Facchinetti
, Domenico Salvagnin
, Giovanni Sparacino
, Simone Del Favero
:
A strategy based on integer programming for optimal dosing and timing of preventive hypoglycemic treatments in type 1 diabetes management. Comput. Methods Programs Biomed. 250: 108179 (2024) - [j44]Nunzio Camerlingo, Martina Vettoretti, Simone Del Favero, Andrea Facchinetti, Pratik Choudhary
, Giovanni Sparacino:
Corrigendum to "Generation of post-meal insulin correction boluses in type 1 diabetes simulation models for in-silico clinical trials: More realistic scenarios obtained using a decision tree approach". Comput. Methods Programs Biomed. 252: 108232 (2024) - 2023
- [j43]Martina Vettoretti, Martina Drecogna
, Simone Del Favero
, Andrea Facchinetti
, Giovanni Sparacino
:
A Markov Model of Gap Occurrence in Continuous Glucose Monitoring Data for Realistic in Silico Clinical Trials. Comput. Methods Programs Biomed. 240: 107700 (2023) - [j42]Isotta Trescato
, Chiara Roversi, Martina Vettoretti, Barbara Di Camillo, Andrea Facchinetti:
A model to forecast the two-year variation of subjective wellbeing in the elderly population. BMC Medical Informatics Decis. Mak. 23(1): 253 (2023) - [j41]Giacomo Cappon
, Francesco Prendin
, Andrea Facchinetti
, Giovanni Sparacino
, Simone Del Favero
:
Individualized Models for Glucose Prediction in Type 1 Diabetes: Comparing Black-Box Approaches to a Physiological White-Box One. IEEE Trans. Biomed. Eng. 70(11): 3105-3115 (2023) - [j40]Giacomo Cappon
, Martina Vettoretti
, Giovanni Sparacino
, Simone Del Favero
, Andrea Facchinetti
:
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. 70(11): 3227-3238 (2023) - [j39]Jacopo Pavan
, Domenico Salvagnin
, Andrea Facchinetti
, Giovanni Sparacino
, Simone Del Favero
:
Incorporating Sparse and Quantized Carbohydrates Suggestions in Model Predictive Control for Artificial Pancreas in Type 1 Diabetes. IEEE Trans. Control. Syst. Technol. 31(2): 570-586 (2023) - [j38]Giulia Noaro
, Taiyu Zhu
, Giacomo Cappon
, Andrea Facchinetti
, Pantelis Georgiou
:
A Personalized and Adaptive Insulin Bolus Calculator Based on Double Deep Q- Learning to Improve Type 1 Diabetes Management. IEEE J. Biomed. Health Informatics 27(5): 2536-2544 (2023) - [c31]Giacomo Cappon, Elisa Pellizzari, Luca Cossu, Giovanni Sparacino, Annalisa Deodati, Riccardo Schiaffini, Stefano Cianfarani, Andrea Facchinetti:
System Architecture of TWIN: A New Digital Twin-Based Clinical Decision Support System for Type 1 Diabetes Management in Children. BSN 2023: 1-4 - [c30]Elena Idi, Francesco Prendin, Andrea Facchinetti, Giovanni Sparacino, Simone Del Favero:
Detection of compression artifacts in time-series data from continuous glucose monitoring sensors using matched filters. BSN 2023: 1-4 - [c29]Elisa Pellizzari, Francesco Prendin, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti:
A Deep-Learning Based Algorithm for the Management of Hyperglycemia in Type 1 Diabetes Therapy. BSN 2023: 1-4 - 2022
- [j37]Simone Faccioli
, Iván Sala-Mira
, José-Luis Díez, Andrea Facchinetti
, Giovanni Sparacino
, Simone Del Favero
, Jorge Bondia
:
Super-twisting-based meal detector for type 1 diabetes management: Improvement and assessment in a real-life scenario. Comput. Methods Programs Biomed. 219: 106736 (2022) - [j36]Nunzio Camerlingo, Martina Vettoretti, Simone Del Favero
, Andrea Facchinetti, Pratik Choudhary
, Giovanni Sparacino
:
Generation of post-meal insulin correction boluses in type 1 diabetes simulation models for in-silico clinical trials: More realistic scenarios obtained using a decision tree approach. Comput. Methods Programs Biomed. 221: 106862 (2022) - [j35]Francesco Prendin
, José-Luis Díez
, Simone Del Favero
, Giovanni Sparacino
, Andrea Facchinetti
, Jorge Bondia
:
Assessment of Seasonal Stochastic Local Models for Glucose Prediction without Meal Size Information under Free-Living Conditions. Sensors 22(22): 8682 (2022) - [j34]Simone Faccioli
, Andrea Facchinetti
, Giovanni Sparacino
, Gianluigi Pillonetto
, Simone Del Favero
:
Linear Model Identification for Personalized Prediction and Control in Diabetes. IEEE Trans. Biomed. Eng. 69(2): 558-568 (2022) - 2021
- [j33]Francesco Prendin
, Simone Del Favero
, Martina Vettoretti
, Giovanni Sparacino
, Andrea Facchinetti
:
Forecasting of Glucose Levels and Hypoglycemic Events: Head-to-Head Comparison of Linear and Nonlinear Data-Driven Algorithms Based on Continuous Glucose Monitoring Data Only. Sensors 21(5): 1647 (2021) - [j32]Lorenzo Meneghetti
, Andrea Facchinetti
, Simone Del Favero
:
Model-Based Detection and Classification of Insulin Pump Faults and Missed Meal Announcements in Artificial Pancreas Systems for Type 1 Diabetes Therapy. IEEE Trans. Biomed. Eng. 68(1): 170-180 (2021) - [j31]Giulia Noaro
, Giacomo Cappon
, Martina Vettoretti
, Giovanni Sparacino
, Simone Del Favero
, Andrea Facchinetti
:
Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy. IEEE Trans. Biomed. Eng. 68(1): 247-255 (2021) - [c28]Chiara Roversi, Martina Vettoretti, Barbara Di Camillo, Andrea Facchinetti:
Predicting hypertension onset using logistic regression models with labs and/or easily accessible variables: the role of blood pressure measurements. BHI 2021: 1-4 - [c27]Nunzio Camerlingo, Martina Vettoretti, Giovanni Sparacino, Andrea Facchinetti, Julia K. Mader
, Pratik Choudhary
, Simone Del Favero
:
A Mathematical Formula to Determine the Minimum Continuous Glucose Monitoring Duration to Assess Time-in-ranges: Sensitivity Analysis Over the Parameters. EMBC 2021: 1435-1438 - [c26]Giulia Noaro, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti:
An Ensemble Learning Algorithm Based on Dynamic Voting for Targeting the Optimal Insulin Dosage in Type 1 Diabetes Management. EMBC 2021: 1828-1831 - [c25]Giacomo Cappon, Emanuele Pighin, Francesco Prendin, Giovanni Sparacino, Andrea Facchinetti:
A Correction Insulin Bolus Delivery Strategy for Decision Support Systems in Type 1 Diabetes. EMBC 2021: 1832-1835 - [c24]Giacomo Cappon, Giulia Noaro, Nunzio Camerlingo, Luca Cossu
, Giovanni Sparacino, Andrea Facchinetti:
A New Decision Support System for Type 1 Diabetes Management. EMBC 2021: 1993-1996 - [c23]Martina Drecogna, Martina Vettoretti, Simone Del Favero
, Andrea Facchinetti, Giovanni Sparacino:
Data Gap Modeling in Continuous Glucose Monitoring Sensor Data. EMBC 2021: 4379-4382 - 2020
- [j30]Martina Vettoretti
, Giacomo Cappon
, Andrea Facchinetti
, Giovanni Sparacino
:
Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors. Sensors 20(14): 3870 (2020) - [c22]Giacomo Cappon, Lorenzo Meneghetti, Francesco Prendin, Jacopo Pavan, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti:
A Personalized and Interpretable Deep Learning Based Approach to Predict Blood Glucose Concentration in Type 1 Diabetes. KDH@ECAI 2020: 75-79 - [c21]Jacopo Pavan, Francesco Prendin, Lorenzo Meneghetti, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti, Simone Del Favero:
Personalized Machine Learning Algorithm based on Shallow Network and Error Imputation Module for an Improved Blood Glucose Prediction. KDH@ECAI 2020: 95-99 - [c20]Giulia Noaro
, Giacomo Cappon
, Giovanni Sparacino, Simone Del Favero
, Andrea Facchinetti:
Nonlinear Machine Learning Models for Insulin Bolus Estimation in Type 1 Diabetes Therapy. EMBC 2020: 5502-5505
2010 – 2019
- 2019
- [j29]Giuseppe Fico
, Liss Hernández, Jorge Cancela, Arianna Dagliati
, Lucia Sacchi
, Antonio Martinez-Millana, Jorge Posada, Lidia Manero, Jose Verdú, Andrea Facchinetti, Manuel Ottaviano
, Konstantia Zarkogianni, Konstantina S. Nikita
, Leif Groop, Rafael Gabriel, Luca Chiovato
, Vicente Traver, Juan Francisco Merino-Torres
, Claudio Cobelli, Riccardo Bellazzi
, María Teresa Arredondo
:
What do healthcare professionals need to turn risk models for type 2 diabetes into usable computerized clinical decision support systems? Lessons learned from the MOSAIC project. BMC Medical Informatics Decis. Mak. 19(1): 163:1-163:16 (2019) - [j28]Giacomo Cappon
, Andrea Facchinetti
, Giovanni Sparacino
, Pantelis Georgiou
, Pau Herrero
:
Classification of Postprandial Glycemic Status with Application to Insulin Dosing in Type 1 Diabetes - An In Silico Proof-of-Concept. Sensors 19(14): 3168 (2019) - [j27]Giada Acciaroli, Mattia Zanon
, Andrea Facchinetti
, Andreas Caduff, Giovanni Sparacino
:
Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device. Sensors 19(17): 3677 (2019) - [j26]Martina Vettoretti
, Cristina Battocchio, Giovanni Sparacino
, Andrea Facchinetti
:
Development of an Error Model for a Factory-Calibrated Continuous Glucose Monitoring Sensor with 10-Day Lifetime. Sensors 19(23): 5320 (2019) - [j25]Matteo Gadaleta
, Andrea Facchinetti, Enrico Grisan
, Michele Rossi
:
Prediction of Adverse Glycemic Events From Continuous Glucose Monitoring Signal. IEEE J. Biomed. Health Informatics 23(2): 650-659 (2019) - [c19]Martina Vettoretti
, Simone Del Favero
, Giovanni Sparacino, Andrea Facchinetti:
Modeling the error of factory-calibrated continuous glucose monitoring sensors: application to Dexcom G6 sensor data. EMBC 2019: 750-753 - [c18]Nunzio Camerlingo, Martina Vettoretti
, Simone Del Favero
, Giacomo Cappon
, Giovanni Sparacino, Andrea Facchinetti:
In-silico Assessment of Preventive Hypotreatment Efficacy and Development of a Continuous Glucose Monitoring Based Algorithm to Prevent/Mitigate Hypoglycemia in Type 1 Diabetes. EMBC 2019: 4133-4136 - [c17]Giacomo Cappon
, Andrea Facchinetti, Giovanni Sparacino, Simone Del Favero
:
A Bayesian Framework to Identify Type 1 Diabetes Physiological Models Using Easily Accessible Patient Data. EMBC 2019: 6914-6917 - 2018
- [j24]Enrico Longato
, Giada Acciaroli, Andrea Facchinetti, Liisa Hakaste, Tuomi Tiinamaija
, Alberto Maran
, Giovanni Sparacino:
Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data. Comput. Biol. Medicine 96: 141-146 (2018) - [j23]Giada Acciaroli, Martina Vettoretti
, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli
:
Reduction of Blood Glucose Measurements to Calibrate Subcutaneous Glucose Sensors: A Bayesian Multiday Framework. IEEE Trans. Biomed. Eng. 65(3): 587-595 (2018) - [j22]Martina Vettoretti
, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli
:
Type-1 Diabetes Patient Decision Simulator for In Silico Testing Safety and Effectiveness of Insulin Treatments. IEEE Trans. Biomed. Eng. 65(6): 1281-1290 (2018) - [c16]Giacomo Cappon
, Martina Vettoretti
, Francesca Marturano
, Andrea Facchinetti, Giovanni Sparacino:
Optimal Insulin Bolus Dosing in Type 1 Diabetes Management: Neural Network Approach Exploiting CGM Sensor Information. EMBC 2018: 1-4 - [c15]Giada Acciaroli, Martina Vettoretti
, Andrea Facchinetti, Giovanni Sparacino:
Bayesian Model Selection Framework to Improve Calibration of Continuous Glucose Monitoring Sensors for Diabetes Management. EMBC 2018: 29-32 - [c14]Giada Acciaroli, Andrea Facchinetti, Gianluigi Pillonetto, Giovanni Sparacino:
Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models. EMBC 2018: 3630-3633 - [c13]Martina Vettoretti
, Enrico Longato
, Barbara Di Camillo, Andrea Facchinetti:
Importance of Recalibrating Models for Type 2 Diabetes Onset Prediction: Application of the Diabetes Population Risk Tool on the Health and Retirement Study. EMBC 2018: 5358-5361 - 2017
- [j21]Lyvia Biagi, Charrise Mary Ramkissoon
, Andrea Facchinetti
, Yenny Leal
, Josep Vehí
:
Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor. Sensors 17(6): 1361 (2017) - [c12]Eleonora Losiouk
, Giordano Lanzola, Alfonso Galderisi
, Daniele Trevisanuto
, Garry M. Steil, Andrea Facchinetti, Claudio Cobelli:
A telemonitoring service supporting preterm newborns care in a neonatal intensive care unit. RTSI 2017: 1-6 - 2016
- [j20]Giordano Lanzola, Eleonora Losiouk
, Simone Del Favero
, Andrea Facchinetti, Alfonso Galderisi
, Silvana Quaglini, Lalo Magni, Claudio Cobelli:
Remote Blood Glucose Monitoring in mHealth Scenarios: A Review. Sensors 16(12): 1983 (2016) - [j19]Andrea Facchinetti
:
Continuous Glucose Monitoring Sensors: Past, Present and Future Algorithmic Challenges. Sensors 16(12): 2093 (2016) - [j18]Martina Vettoretti
, Andrea Facchinetti, Simone Del Favero
, Giovanni Sparacino, Claudio Cobelli:
Online Calibration of Glucose Sensors From the Measured Current by a Time-Varying Calibration Function and Bayesian Priors. IEEE Trans. Biomed. Eng. 63(8): 1631-1641 (2016) - 2015
- [j17]Andrea Facchinetti, Simone Del Favero
, Giovanni Sparacino, Claudio Cobelli:
Model of glucose sensor error components: identification and assessment for new Dexcom G4 generation devices. Medical Biol. Eng. Comput. 53(12): 1259-1269 (2015) - [c11]Francesco Sambo, Andrea Facchinetti, Liisa Hakaste, Jasmina Kravic, Barbara Di Camillo, Giuseppe Fico
, Jaakko Tuomilehto, Leif Groop, Rafael Gabriel, Tuomi Tiinamaija, Claudio Cobelli:
A Bayesian Network for Probabilistic Reasoning and Imputation of Missing Risk Factors in Type 2 Diabetes. AIME 2015: 172-176 - [c10]Francesco Sambo, Barbara Di Camillo, Alberto Franzin, Andrea Facchinetti, Liisa Hakaste, Jasmina Kravic, Giuseppe Fico
, Jaakko Tuomilehto, Leif Groop, Rafael Gabriel, Tuomi Tiinamaija, Claudio Cobelli:
A Bayesian Network analysis of the probabilistic relations between risk factors in the predisposition to type 2 diabetes. EMBC 2015: 2119-2122 - [c9]Martina Vettoretti
, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Accuracy of devices for self-monitoring of blood glucose: A stochastic error model. EMBC 2015: 2359-2362 - [c8]Martina Vettoretti
, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Patient decision-making of CGM sensor driven insulin therapies in type 1 diabetes: In silico assessment. EMBC 2015: 2363-2366 - 2014
- [j16]Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Jump neural network for online short-time prediction of blood glucose from continuous monitoring sensors and meal information. Comput. Methods Programs Biomed. 113(1): 144-152 (2014) - [j15]Andrea Facchinetti, Simone Del Favero
, Giovanni Sparacino, Jessica Castle, W. Kenneth Ward, Claudio Cobelli:
Modeling the Glucose Sensor Error. IEEE Trans. Biomed. Eng. 61(3): 620-629 (2014) - [j14]Simone Del Favero
, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Improving Accuracy and Precision of Glucose Sensor Profiles: Retrospective Fitting by Constrained Deconvolution. IEEE Trans. Biomed. Eng. 61(4): 1044-1053 (2014) - [c7]Miguel M. Isabel, Jorge Cancela, Giuseppe Fico
, Andrea Facchinetti, Claudio Cobelli, María Teresa Arredondo
:
Can continuous glucose monitoring identify risk factors in type 1 and type 2 diabetes? A literature review. BHI 2014: 248-251 - [c6]Chiara Fabris, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Sparse Principal Component Analysis for the parsimonious description of glucose variability in diabetes. EMBC 2014: 6643-6646 - 2013
- [j13]Mattia Zanon
, Giovanni Sparacino
, Andrea Facchinetti
, Mark Talary
, Andreas Caduff
, Claudio Cobelli
:
Regularised Model Identification Improves Accuracy of Multisensor Systems for Noninvasive Continuous Glucose Monitoring in Diabetes Management. J. Appl. Math. 2013: 793869:1-793869:10 (2013) - [j12]Mattia Zanon, Giovanni Sparacino
, Andrea Facchinetti
, Mark Talary, Martin Mueller, Andreas Caduff, Claudio Cobelli:
Non-Invasive Continuous Glucose Monitoring with Multi-Sensor Systems: A Monte Carlo-Based Methodology for Assessing Calibration Robustness. Sensors 13(6): 7279-7295 (2013) - [j11]Andrea Facchinetti, Simone Del Favero
, Giovanni Sparacino, Claudio Cobelli:
An Online Failure Detection Method of the Glucose Sensor-Insulin Pump System: Improved Overnight Safety of Type-1 Diabetic Subjects. IEEE Trans. Biomed. Eng. 60(2): 406-416 (2013) - [c5]Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Neural Network for Prediction of Glucose Concentration in Type 1 Diabetic Patients. SCAI 2013: 303-306 - 2012
- [j10]Marco Falda
, Stefano Toppo
, Alessandro Pescarolo, Enrico Lavezzo
, Barbara Di Camillo, Andrea Facchinetti, Elisa Cilia, Riccardo Velasco
, Paolo Fontana:
Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms. BMC Bioinform. 13(S-4): S14 (2012) - [j9]Mattia Zanon, Giovanni Sparacino, Andrea Facchinetti, Michela Riz, Mark Talary, Roland E. Suri
, Andreas Caduff, Claudio Cobelli:
Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system. Medical Biol. Eng. Comput. 50(10): 1047-1057 (2012) - [j8]Giovanni Sparacino
, Mattia Zanon, Andrea Facchinetti
, Chiara Zecchin
, Alberto Maran
, Claudio Cobelli:
Italian Contributions to the Development of Continuous Glucose Monitoring Sensors for Diabetes Management. Sensors 12(10): 13753-13780 (2012) - [j7]Simone Del Favero
, Andrea Facchinetti, Claudio Cobelli:
A Glucose-Specific Metric to Assess Predictors and Identify Models. IEEE Trans. Biomed. Eng. 59(5): 1281-1290 (2012) - [j6]Chiara Zecchin
, Andrea Facchinetti, Giovanni Sparacino, Giuseppe De Nicolao, Claudio Cobelli:
Neural Network Incorporating Meal Information Improves Accuracy of Short-Time Prediction of Glucose Concentration. IEEE Trans. Biomed. Eng. 59(6): 1550-1560 (2012) - [j5]Stefania Guerra, Andrea Facchinetti, Giovanni Sparacino, Giuseppe De Nicolao, Claudio Cobelli:
Enhancing the Accuracy of Subcutaneous Glucose Sensors: A Real-Time Deconvolution-Based Approach. IEEE Trans. Biomed. Eng. 59(6): 1658-1669 (2012) - 2011
- [j4]Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Online Denoising Method to Handle Intraindividual Variability of Signal-to-Noise Ratio in Continuous Glucose Monitoring. IEEE Trans. Biomed. Eng. 58(9): 2664-2671 (2011) - [c4]Mattia Zanon, Michela Riz, Giovanni Sparacino, Andrea Facchinetti, Roland E. Suri
, Mark S. Talary, Claudio Cobelli:
Assessment of linear regression techniques for modeling multisensor data for non-invasive continuous glucose monitoring. EMBC 2011: 2538-2541 - [c3]Andrea Facchinetti, Simone Del Favero
, Giovanni Sparacino, Claudio Cobelli:
Detecting failures of the glucose sensor-insulin pump system: Improved overnight safety monitoring for Type-1 diabetes. EMBC 2011: 4947-4950 - [c2]Chiara Zecchin
, Andrea Facchinetti, Giovanni Sparacino, Giuseppe De Nicolao, Claudio Cobelli:
A new neural network approach for short-term glucose prediction using continuous glucose monitoring time-series and meal information. EMBC 2011: 5653-5656 - 2010
- [j3]Giovanni Sparacino
, Andrea Facchinetti, Claudio Cobelli:
"Smart" Continuous Glucose Monitoring Sensors: On-Line Signal Processing Issues. Sensors 10(7): 6751-6772 (2010) - [j2]Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
An Online Self-Tunable Method to Denoise CGM Sensor Data. IEEE Trans. Biomed. Eng. 57(3): 634-641 (2010)
2000 – 2009
- 2007
- [j1]Giovanni Sparacino, Francesca Zanderigo
, Stefano Corazza, Alberto Maran
, Andrea Facchinetti, Claudio Cobelli:
Glucose Concentration can be Predicted Ahead in Time From Continuous Glucose Monitoring Sensor Time-Series. IEEE Trans. Biomed. Eng. 54(5): 931-937 (2007) - 2006
- [c1]Andrea Facchinetti, Giovanni Sparacino, Francesca Zanderigo
, Claudio Cobelli:
Reconstructing by Deconvolution Plasma Glucose from Continuous Glucose Monitoring Sensor Data. EMBC 2006: 55-58
Coauthor Index
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