Reconstructing by Deconvolution Plasma Glucose from Continuous Glucose Monitoring Sensor Data. - Andrea Facchinetti; Giovanni Sparacino; Francesca Zanderigo; Claudio Cobelli (EMBC, 2006)

Glucose Concentration can be Predicted Ahead in Time From Continuous Glucose Monitoring Sensor Time-Series. - Giovanni Sparacino; Francesca Zanderigo; Stefano Corazza; Alberto Maran; Andrea Facchinetti; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2007)

"Smart" Continuous Glucose Monitoring Sensors: On-Line Signal Processing Issues. - Giovanni Sparacino; Andrea Facchinetti; Claudio Cobelli (Sensors, 2010)

An Online Self-Tunable Method to Denoise CGM Sensor Data. - Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2010)

Detecting failures of the glucose sensor-insulin pump system: Improved overnight safety monitoring for Type-1 diabetes. - Andrea Facchinetti; Simone Del Favero; Giovanni Sparacino; Claudio Cobelli (EMBC, 2011)

Assessment of linear regression techniques for modeling multisensor data for non-invasive continuous glucose monitoring. - Mattia Zanon; Michela Riz; Giovanni Sparacino; Andrea Facchinetti; Roland E. Suri; Mark S. Talary; Claudio Cobelli (EMBC, 2011)

A new neural network approach for short-term glucose prediction using continuous glucose monitoring time-series and meal information. - Chiara Zecchin; Andrea Facchinetti; Giovanni Sparacino; Giuseppe De Nicolao; Claudio Cobelli (EMBC, 2011)

Online Denoising Method to Handle Intraindividual Variability of Signal-to-Noise Ratio in Continuous Glucose Monitoring. - Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2011)

Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms. - Marco Falda; Stefano Toppo; Alessandro Pescarolo; Enrico Lavezzo; Barbara Di Camillo; Andrea Facchinetti; Elisa Cilia; Riccardo Velasco; Paolo Fontana (BMC Bioinform., 2012)

Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system. - Mattia Zanon; Giovanni Sparacino; Andrea Facchinetti; Michela Riz; Mark Talary; Roland E. Suri; Andreas Caduff; Claudio Cobelli (Medical Biol. Eng. Comput., 2012)

Italian Contributions to the Development of Continuous Glucose Monitoring Sensors for Diabetes Management. - Giovanni Sparacino; Mattia Zanon; Andrea Facchinetti; Chiara Zecchin; Alberto Maran; Claudio Cobelli (Sensors, 2012)

A Glucose-Specific Metric to Assess Predictors and Identify Models. - Simone Del Favero; Andrea Facchinetti; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2012)

Enhancing the Accuracy of Subcutaneous Glucose Sensors: A Real-Time Deconvolution-Based Approach. - Stefania Guerra; Andrea Facchinetti; Giovanni Sparacino; Giuseppe De Nicolao; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2012)

Neural Network Incorporating Meal Information Improves Accuracy of Short-Time Prediction of Glucose Concentration. - Chiara Zecchin; Andrea Facchinetti; Giovanni Sparacino; Giuseppe De Nicolao; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2012)

Neural Network for Prediction of Glucose Concentration in Type 1 Diabetic Patients. - Chiara Zecchin; Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (SCAI, 2013)

Regularised Model Identification Improves Accuracy of Multisensor Systems for Noninvasive Continuous Glucose Monitoring in Diabetes Management. - Mattia Zanon; Giovanni Sparacino; Andrea Facchinetti; Mark Talary; Andreas Caduff; Claudio Cobelli (J. Appl. Math., 2013)

Non-Invasive Continuous Glucose Monitoring with Multi-Sensor Systems: A Monte Carlo-Based Methodology for Assessing Calibration Robustness. - Mattia Zanon; Giovanni Sparacino; Andrea Facchinetti; Mark Talary; Martin Mueller; Andreas Caduff; Claudio Cobelli (Sensors, 2013)

An Online Failure Detection Method of the Glucose Sensor-Insulin Pump System: Improved Overnight Safety of Type-1 Diabetic Subjects. - Andrea Facchinetti; Simone Del Favero; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2013)

Can continuous glucose monitoring identify risk factors in type 1 and type 2 diabetes? A literature review. - Miguel M. Isabel; Jorge Cancela; Giuseppe Fico; Andrea Facchinetti; Claudio Cobelli; María Teresa Arredondo (BHI, 2014)

Sparse Principal Component Analysis for the parsimonious description of glucose variability in diabetes. - Chiara Fabris; Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (EMBC, 2014)

Jump neural network for online short-time prediction of blood glucose from continuous monitoring sensors and meal information. - Chiara Zecchin; Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (Comput. Methods Programs Biomed., 2014)

Modeling the Glucose Sensor Error. - Andrea Facchinetti; Simone Del Favero; Giovanni Sparacino; Jessica Castle; W. Kenneth Ward; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2014)

Improving Accuracy and Precision of Glucose Sensor Profiles: Retrospective Fitting by Constrained Deconvolution. - Simone Del Favero; Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2014)

A Bayesian Network for Probabilistic Reasoning and Imputation of Missing Risk Factors in Type 2 Diabetes. - Francesco Sambo; Andrea Facchinetti; Liisa Hakaste; Jasmina Kravic; Barbara Di Camillo; Giuseppe Fico; Jaakko Tuomilehto; Leif Groop; Rafael Gabriel; Tuomi Tiinamaija; Claudio Cobelli (AIME, 2015)

A Bayesian Network analysis of the probabilistic relations between risk factors in the predisposition to type 2 diabetes. - 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 (EMBC, 2015)

Accuracy of devices for self-monitoring of blood glucose: A stochastic error model. - Martina Vettoretti; Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (EMBC, 2015)

Patient decision-making of CGM sensor driven insulin therapies in type 1 diabetes: In silico assessment. - Martina Vettoretti; Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (EMBC, 2015)

Model of glucose sensor error components: identification and assessment for new Dexcom G4 generation devices. - Andrea Facchinetti; Simone Del Favero; Giovanni Sparacino; Claudio Cobelli (Medical Biol. Eng. Comput., 2015)

Continuous Glucose Monitoring Sensors: Past, Present and Future Algorithmic Challenges. - Andrea Facchinetti (Sensors, 2016)

Remote Blood Glucose Monitoring in mHealth Scenarios: A Review. - Giordano Lanzola; Eleonora Losiouk; Simone Del Favero; Andrea Facchinetti; Alfonso Galderisi; Silvana Quaglini; Lalo Magni; Claudio Cobelli (Sensors, 2016)

Online Calibration of Glucose Sensors From the Measured Current by a Time-Varying Calibration Function and Bayesian Priors. - Martina Vettoretti; Andrea Facchinetti; Simone Del Favero; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2016)

A telemonitoring service supporting preterm newborns care in a neonatal intensive care unit. - Eleonora Losiouk; Giordano Lanzola; Alfonso Galderisi; Daniele Trevisanuto; Garry M. Steil; Andrea Facchinetti; Claudio Cobelli (RTSI, 2017)

Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor. - Lyvia Biagi; Charrise Mary Ramkissoon; Andrea Facchinetti; Yenny Leal; Josep Vehí (Sensors, 2017)

Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models. - Giada Acciaroli; Andrea Facchinetti; Gianluigi Pillonetto; Giovanni Sparacino (EMBC, 2018)

Bayesian Model Selection Framework to Improve Calibration of Continuous Glucose Monitoring Sensors for Diabetes Management. - Giada Acciaroli; Martina Vettoretti; Andrea Facchinetti; Giovanni Sparacino (EMBC, 2018)

Optimal Insulin Bolus Dosing in Type 1 Diabetes Management: Neural Network Approach Exploiting CGM Sensor Information. - Giacomo Cappon; Martina Vettoretti; Francesca Marturano; Andrea Facchinetti; Giovanni Sparacino (EMBC, 2018)

Importance of Recalibrating Models for Type 2 Diabetes Onset Prediction: Application of the Diabetes Population Risk Tool on the Health and Retirement Study. - Martina Vettoretti; Enrico Longato; Barbara Di Camillo; Andrea Facchinetti (EMBC, 2018)

Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data. - Enrico Longato; Giada Acciaroli; Andrea Facchinetti; Liisa Hakaste; Tuomi Tiinamaija; Alberto Maran; Giovanni Sparacino (Comput. Biol. Medicine, 2018)

Reduction of Blood Glucose Measurements to Calibrate Subcutaneous Glucose Sensors: A Bayesian Multiday Framework. - Giada Acciaroli; Martina Vettoretti; Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2018)

Type-1 Diabetes Patient Decision Simulator for In Silico Testing Safety and Effectiveness of Insulin Treatments. - Martina Vettoretti; Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2018)

In-silico Assessment of Preventive Hypotreatment Efficacy and Development of a Continuous Glucose Monitoring Based Algorithm to Prevent/Mitigate Hypoglycemia in Type 1 Diabetes. - Nunzio Camerlingo; Martina Vettoretti; Simone Del Favero; Giacomo Cappon; Giovanni Sparacino; Andrea Facchinetti (EMBC, 2019)

A Bayesian Framework to Identify Type 1 Diabetes Physiological Models Using Easily Accessible Patient Data. - Giacomo Cappon; Andrea Facchinetti; Giovanni Sparacino; Simone Del Favero (EMBC, 2019)

Modeling the error of factory-calibrated continuous glucose monitoring sensors: application to Dexcom G6 sensor data. - Martina Vettoretti; Simone Del Favero; Giovanni Sparacino; Andrea Facchinetti (EMBC, 2019)

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. - 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; et al. (BMC Medical Informatics Decis. Mak., 2019)

Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device. - Giada Acciaroli; Mattia Zanon; Andrea Facchinetti; Andreas Caduff; Giovanni Sparacino (Sensors, 2019)

Classification of Postprandial Glycemic Status with Application to Insulin Dosing in Type 1 Diabetes - An In Silico Proof-of-Concept. - Giacomo Cappon; Andrea Facchinetti; Giovanni Sparacino; Pantelis Georgiou; Pau Herrero (Sensors, 2019)

Development of an Error Model for a Factory-Calibrated Continuous Glucose Monitoring Sensor with 10-Day Lifetime. - Martina Vettoretti; Cristina Battocchio; Giovanni Sparacino; Andrea Facchinetti (Sensors, 2019)

Prediction of Adverse Glycemic Events From Continuous Glucose Monitoring Signal. - Matteo Gadaleta; Andrea Facchinetti; Enrico Grisan; Michele Rossi (IEEE J. Biomed. Health Informatics, 2019)

A Personalized and Interpretable Deep Learning Based Approach to Predict Blood Glucose Concentration in Type 1 Diabetes. - Giacomo Cappon; Lorenzo Meneghetti; Francesco Prendin; Jacopo Pavan; Giovanni Sparacino; Simone Del Favero; Andrea Facchinetti (KDH@ECAI, 2020)

Personalized Machine Learning Algorithm based on Shallow Network and Error Imputation Module for an Improved Blood Glucose Prediction. - Jacopo Pavan; Francesco Prendin; Lorenzo Meneghetti; Giacomo Cappon; Giovanni Sparacino; Andrea Facchinetti; Simone Del Favero (KDH@ECAI, 2020)

Nonlinear Machine Learning Models for Insulin Bolus Estimation in Type 1 Diabetes Therapy. - Giulia Noaro; Giacomo Cappon; Giovanni Sparacino; Simone Del Favero; Andrea Facchinetti (EMBC, 2020)

Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors. - Martina Vettoretti; Giacomo Cappon; Andrea Facchinetti; Giovanni Sparacino (Sensors, 2020)

Predicting hypertension onset using logistic regression models with labs and/or easily accessible variables: the role of blood pressure measurements. - Chiara Roversi; Martina Vettoretti; Barbara Di Camillo; Andrea Facchinetti (BHI, 2021)

A Mathematical Formula to Determine the Minimum Continuous Glucose Monitoring Duration to Assess Time-in-ranges: Sensitivity Analysis Over the Parameters. - Nunzio Camerlingo; Martina Vettoretti; Giovanni Sparacino; Andrea Facchinetti; Julia K. Mader; Pratik Choudhary; Simone Del Favero (EMBC, 2021)

A New Decision Support System for Type 1 Diabetes Management. - Giacomo Cappon; Giulia Noaro; Nunzio Camerlingo; Luca Cossu; Giovanni Sparacino; Andrea Facchinetti (EMBC, 2021)

A Correction Insulin Bolus Delivery Strategy for Decision Support Systems in Type 1 Diabetes. - Giacomo Cappon; Emanuele Pighin; Francesco Prendin; Giovanni Sparacino; Andrea Facchinetti (EMBC, 2021)

Data Gap Modeling in Continuous Glucose Monitoring Sensor Data. - Martina Drecogna; Martina Vettoretti; Simone Del Favero; Andrea Facchinetti; Giovanni Sparacino (EMBC, 2021)

An Ensemble Learning Algorithm Based on Dynamic Voting for Targeting the Optimal Insulin Dosage in Type 1 Diabetes Management. - Giulia Noaro; Giacomo Cappon; Giovanni Sparacino; Andrea Facchinetti (EMBC, 2021)

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. - Francesco Prendin; Simone Del Favero; Martina Vettoretti; Giovanni Sparacino; Andrea Facchinetti (Sensors, 2021)

Model-Based Detection and Classification of Insulin Pump Faults and Missed Meal Announcements in Artificial Pancreas Systems for Type 1 Diabetes Therapy. - Lorenzo Meneghetti; Andrea Facchinetti; Simone Del Favero (IEEE Trans. Biomed. Eng., 2021)

Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy. - Giulia Noaro; Giacomo Cappon; Martina Vettoretti; Giovanni Sparacino; Simone Del Favero; Andrea Facchinetti (IEEE Trans. Biomed. Eng., 2021)

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. - Nunzio Camerlingo; Martina Vettoretti; Simone Del Favero; Andrea Facchinetti; Pratik Choudhary; Giovanni Sparacino (Comput. Methods Programs Biomed., 2022)

Super-twisting-based meal detector for type 1 diabetes management: Improvement and assessment in a real-life scenario. - Simone Faccioli; Iván Sala-Mira; José-Luis Díez; Andrea Facchinetti; Giovanni Sparacino; Simone Del Favero; Jorge Bondia (Comput. Methods Programs Biomed., 2022)

Assessment of Seasonal Stochastic Local Models for Glucose Prediction without Meal Size Information under Free-Living Conditions. - Francesco Prendin; José-Luis Díez; Simone Del Favero; Giovanni Sparacino; Andrea Facchinetti; Jorge Bondia (Sensors, 2022)

Linear Model Identification for Personalized Prediction and Control in Diabetes. - Simone Faccioli; Andrea Facchinetti; Giovanni Sparacino; Gianluigi Pillonetto; Simone Del Favero (IEEE Trans. Biomed. Eng., 2022)

System Architecture of TWIN: A New Digital Twin-Based Clinical Decision Support System for Type 1 Diabetes Management in Children. - Giacomo Cappon; Elisa Pellizzari; Luca Cossu; Giovanni Sparacino; Annalisa Deodati; Riccardo Schiaffini; Stefano Cianfarani; Andrea Facchinetti (BSN, 2023)

Detection of compression artifacts in time-series data from continuous glucose monitoring sensors using matched filters. - Elena Idi; Francesco Prendin; Andrea Facchinetti; Giovanni Sparacino; Simone Del Favero (BSN, 2023)

A Deep-Learning Based Algorithm for the Management of Hyperglycemia in Type 1 Diabetes Therapy. - Elisa Pellizzari; Francesco Prendin; Giacomo Cappon; Giovanni Sparacino; Andrea Facchinetti (BSN, 2023)

BRAINTEASER Architecture for Integration of AI Models and Interactive Tools for Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS) Progression Prediction and Management. - Vladimir Urosevic; Nikola Vojicic; Aleksandar Jovanovic; Borko Kostic; Sergio González-Martínez; María Fernanda Cabrera-Umpiérrez; Manuel Ottaviano; Luca Cossu; Andrea Facchinetti; Giacomo Cappon (ICOST, 2023)

Incorporating Sparse and Quantized Carbohydrates Suggestions in Model Predictive Control for Artificial Pancreas in Type 1 Diabetes. - Jacopo Pavan; Domenico Salvagnin; Andrea Facchinetti; Giovanni Sparacino; Simone Del Favero (IEEE Trans. Control. Syst. Technol., 2023)

A Personalized and Adaptive Insulin Bolus Calculator Based on Double Deep Q- Learning to Improve Type 1 Diabetes Management. - Giulia Noaro; Taiyu Zhu; Giacomo Cappon; Andrea Facchinetti; Pantelis Georgiou (IEEE J. Biomed. Health Informatics, 2023)

A Markov Model of Gap Occurrence in Continuous Glucose Monitoring Data for Realistic in Silico Clinical Trials. - Martina Vettoretti; Martina Drecogna; Simone Del Favero; Andrea Facchinetti; Giovanni Sparacino (Comput. Methods Programs Biomed., 2023)

Individualized Models for Glucose Prediction in Type 1 Diabetes: Comparing Black-Box Approaches to a Physiological White-Box One. - Giacomo Cappon; Francesco Prendin; Andrea Facchinetti; Giovanni Sparacino; Simone Del Favero (IEEE Trans. Biomed. Eng., 2023)

ReplayBG: A Digital Twin-Based Methodology to Identify a Personalized Model From Type 1 Diabetes Data and Simulate Glucose Concentrations to Assess Alternative Therapies. - Giacomo Cappon; Martina Vettoretti; Giovanni Sparacino; Simone Del Favero; Andrea Facchinetti (IEEE Trans. Biomed. Eng., 2023)

A model to forecast the two-year variation of subjective wellbeing in the elderly population. - Isotta Trescato; Chiara Roversi; Martina Vettoretti; Barbara Di Camillo; Andrea Facchinetti (BMC Medical Informatics Decis. Mak., 2023)

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". - Nunzio Camerlingo; Martina Vettoretti; Simone Del Favero; Andrea Facchinetti; Pratik Choudhary; Giovanni Sparacino (Comput. Methods Programs Biomed., 2024)

A strategy based on integer programming for optimal dosing and timing of preventive hypoglycemic treatments in type 1 diabetes management. - Jacopo Pavan; Giulia Noaro; Andrea Facchinetti; Domenico Salvagnin; Giovanni Sparacino; Simone Del Favero (Comput. Methods Programs Biomed., 2024)

Risk of hypoglycemia in type 1 diabetes management: An in-silico sensitivity analysis to assess and rank the quantitative impact of different behavioral factors. - Chiara Roversi; Nunzio Camerlingo; Martina Vettoretti; Andrea Facchinetti; Pratik Choudhary; Giovanni Sparacino; Simone Del Favero (Comput. Methods Programs Biomed., 2024)

Automated pipeline for denoising, missing data processing, and feature extraction for signals acquired via wearable devices in multiple sclerosis and amyotrophic lateral sclerosis applications. - Luca Cossu; Giacomo Cappon; Andrea Facchinetti (Frontiers Digit. Health, 2024)

Addressing Current Unmet Clinical Needs by Co-Designing a Novel Web Interface for Decision Support in Pediatric Type 1 Diabetes. - Luca Cossu; Giacomo Cappon; Elisa Pellizzari; Annalisa Deodati; Riccardo Schiaffini; Stefano Cianfarani; Giovanni Sparacino; Andrea Facchinetti (ICHI, 2025)

Unsupervised Retrospective Detection of Pressure Induced Failures in Continuous Glucose Monitoring Sensors for T1D Management. - Elena Idi; Eleonora Manzoni; Andrea Facchinetti; Giovanni Sparacino; Simone Del Favero (IEEE J. Biomed. Health Informatics, 2025)

Regularized Denoising Method for Retrospective Detection of Pressure Induced Artifacts in Continuous Glucose Monitoring Sensors Data. - Eleonora Manzoni; Elena Idi; Nunzio Camerlingo; Andrea Facchinetti; Giovanni Sparacino; Simone Del Favero (IEEE Trans. Biomed. Eng., 2025)

Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions. - Francesco Prendin; Olivia Streicher; Giacomo Cappon; Eva Rolfes; David Herzig; Lia Bally; Andrea Facchinetti (BMC Medical Informatics Decis. Mak., 2025)