A stochastic deconvolution method to reconstruct insulin secretion rate after a glucose stimulus. - Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 1996)

Nonparametric input estimation in physiological systems: Problems, methods, and case studies. - Giuseppe De Nicolao; Giovanni Sparacino; Claudio Cobelli (Autom., 1997)

Fast spline smoothing via spectral factorization concepts. - Giuseppe De Nicolao; Giancarlo Ferrari-Trecate; Giovanni Sparacino (Autom., 2000)

Maximum-likelihood versus maximum a posteriori parameter estimation of physiological system models: the c-peptide impulse response case study. - Giovanni Sparacino; Chiara Tombolato; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2000)

Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method. - Gianluigi Pillonetto; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 2001)

A Bayesian approach to estimate evoked potentials. - Giovanni Sparacino; Stefano Milani; Edoardo Arslan; Claudio Cobelli (Comput. Methods Programs Biomed., 2002)

WINSTODEC: a stochastic deconvolution interactive program for physiological and pharmacokinetic systems. - Giovanni Sparacino; Gianluigi Pillonetto; Massimo Capello; Giuseppe De Nicolao; Claudio Cobelli (Comput. Methods Programs Biomed., 2002)

"Population" approach improves parameter estimation of kinetic models from dynamic PET data. - Alessandra Bertoldo; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Medical Imaging, 2004)

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

A new dynamic index of insulin sensitivity. - Gianluigi Pillonetto; Andrea Caumo; Giovanni Sparacino; Claudio Cobelli (IEEE Trans. Biomed. Eng., 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)

Electroglottography and microphone signals assessed by approximate entropy in normal and dysphonic subjects. - Giovanni Sparacino; Wladimiro De Colle; D. De Luca; Edoardo Arslan (MAVEBA, 2009)

"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)

A methodology to improve estimation of stimulus-evoked hemodynamic response from fNIRS measurements. - Fabio Scarpa; Sabrina Brigadoi; Simone Cutini; Pietro Scatturin; Marco Zorzi; Roberto Dell'Acqua; Giovanni Sparacino (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)

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)

A novel method for the determination of the EEG individual alpha frequency. - Anahita Goljahani; Costanza D'Avanzo; Sami Schiff; Piero Amodio; Patrizia Silvia Bisiacchi; Giovanni Sparacino (NeuroImage, 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)

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)

Voice disorders assessed by (cross-) Sample Entropy of electroglottogram and microphone signals. - Chiara Fabris; Wladimiro De Colle; Giovanni Sparacino (Biomed. Signal Process. Control., 2013)

A multi-task learning approach for the extraction of single-trial evoked potentials. - Costanza D'Avanzo; Anahita Goljahani; Gianluigi Pillonetto; Giuseppe De Nicolao; Giovanni Sparacino (Comput. Methods Programs Biomed., 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)

A reference-channel based methodology to improve estimation of event-related hemodynamic response from fNIRS measurements. - Fabio Scarpa; Sabrina Brigadoi; Simone Cutini; Pietro Scatturin; Marco Zorzi; Roberto Dell'Acqua; Giovanni Sparacino (NeuroImage, 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)

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

Preprocessing by a Bayesian Single-Trial Event-Related Potential Estimation Technique Allows Feasibility of an Assistive Single-Channel P300-Based Brain-Computer Interface. - Anahita Goljahani; Costanza D'Avanzo; Stefano Silvoni; Paolo Tonin; Francesco Piccione; Giovanni Sparacino (Comput. Math. Methods Medicine, 2014)

An EEGLAB plugin to analyze individual EEG alpha rhythms using the "channel reactivity-based method". - Anahita Goljahani; Patrizia Silvia Bisiacchi; Giovanni Sparacino (Comput. Methods Programs Biomed., 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)

Automated analysis of local field potentials evoked by mechanical whisker stimulation in rat barrel cortex. - Maria Rubega; Claudia Cecchetto; Stefano Vassanelli; Giovanni Sparacino (EMBC, 2015)

Decrease of EEG Coherence during hypoglycemia in type 1 diabetic subjects. - Maria Rubega; Giovanni Sparacino; Anne-Sophie Sejling; Claus Bogh Juhl; 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)

A compressive sensing spectral model for fNIRS haemodynamic response de-noising. - Guglielmo Frigo; Sabrina Brigadoi; Giada Giorgi; Giovanni Sparacino; Claudio Narduzzi (MeMeA, 2015)

A software-based platform for multichannel electrophysiological data acquisition. - Guglielmo Frigo; Maria Rubega; G. Lezziero; Roberto Fontana; Claudia Cecchetto; Stefano Vassanelli; Giovanni Sparacino; Matteo Bertocco (MeMeA, 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)

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)

Measuring Cerebral Activation From fNIRS Signals: An Approach Based on Compressive Sensing and Taylor-Fourier Model. - Guglielmo Frigo; Sabrina Brigadoi; Giada Giorgi; Giovanni Sparacino; Claudio Narduzzi (IEEE Trans. Instrum. Meas., 2016)

Hypoglycemia-induced EEG complexity changes in Type 1 diabetes assessed by fractal analysis algorithm. - Fabio Scarpa; Maria Rubega; Mattia Zanon; Francesca Finotello; Anne-Sophie Sejling; Giovanni Sparacino (Biomed. Signal Process. Control., 2017)

Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation. - Maria Rubega; Claudia Cecchetto; Stefano Vassanelli; Giovanni Sparacino (Source Code Biol. Medicine, 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)

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)

Detecting Undiagnosed Diabetes: Proof-of-Concept Based on the Health-Information Exchange System of the Veneto Region (North-East Italy). - Enrico Longato; Barbara Di Camillo; Giovanni Sparacino; Claudio Saccavini; Arianna Cocchiglia; Lara Tramontan; Gian Paolo Fadini (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)

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)

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)

A Time-Frequency Analysis for the Online Detection of the N2pc Event-Related Potential (ERP) Component in Individual EEG Datasets. - Francesca Marturano; Sabrina Brigadoi; Mattia Doro; Roberto Dell'Acqua; Giovanni Sparacino (EMBC, 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)

Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients. - Maria Rubega; Fabio Scarpa; Debora Teodori; Anne-Sophie Sejling; Christian S. Frandsen; Giovanni Sparacino (Entropy, 2020)

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

Recurrent Neural Network to Predict Renal Function Impairment in Diabetic Patients via Longitudinal Routine Check-up Data. - Enrico Longato; Gian Paolo Fadini; Giovanni Sparacino; Angelo Avogaro; Barbara Di Camillo (AIME, 2021)

Comparing the Predictive Power of Heart Failure Hospitalisation Risk Scores in the Diabetic Outpatient Clinic and Primary Care Settings. - Alessandro Guazzo; Alessandro Battaggia; Enrico Longato; Bruno Franco-Novelletto; Angelo Avogaro; Gian Paolo Fadini; Maurizio Cancian; Barbara Di Camillo; Giovanni Sparacino; Massimo Fusello (BIBM, 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)

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)

A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims. - Enrico Longato; Gian Paolo Fadini; Giovanni Sparacino; Angelo Avogaro; Lara Tramontan; Barbara Di Camillo (IEEE J. Biomed. Health Informatics, 2021)

Data-Driven Supervised Compression Artifacts Detection on Continuous Glucose Sensors. - Elena Idi; Eleonora Manzoni; Giovanni Sparacino; Simone Del Favero (EMBC, 2022)

Sleep spindles changes in people with previous COVID-19 infection. - Maria Rubega; Emanuela Formaggio; Luciana Ciringione; Margherita Bertuccelli; Matilde Paramento; Giovanni Sparacino; Andrea Vianello; Stefano Masiero; Alessandra Del Felice (EMBC, 2022)

Explainable Deep-Learning Model Reveals Past Cardiovascular Disease in Patients with Diabetes Using Free-Form Visit Reports. - Alessandro Guazzo; Enrico Longato; Gian Paolo Fadini; Mario Luca Morieri; Giovanni Sparacino; Barbara Di Camillo (LOD (1), 2022)

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)

Time-series analysis of multidimensional clinical-laboratory data by dynamic Bayesian networks reveals trajectories of COVID-19 outcomes. - Enrico Longato; Mario Luca Morieri; Giovanni Sparacino; Barbara Di Camillo; Annamaria Cattelan; Sara Lo Menzo; Marco Trevenzoli; Andrea Vianello; Gabriella Guarnieri; Federico Lionello; Angelo Avogaro; Paola Fioretto; et al. (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)

Dealing with Data Scarcity in Rare Diseases: Dynamic Bayesian Networks and Transfer Learning to Develop Prognostic Models of Amyotrophic Lateral Sclerosis. - Enrico Longato; Erica Tavazzi; Adriano Chiò; Gabriele Mora; Giovanni Sparacino; Barbara Di Camillo (AIME, 2023)

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)

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 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)

Characterization of Chronic Kidney Disease Progression in Patients with Diabetes via Group-Based Multi-Trajectory Modeling. - Alessandro Guazzo; Enrico Longato; Gian Paolo Fadini; Giovanni Sparacino; Rema Padman; Barbara Di Camillo (EMBC, 2024)

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)

Effect of Clinical History on Predictive Model Performance for Renal Complications of Diabetes. - Davide Dei Cas; Barbara Di Camillo; Gian Paolo Fadini; Giovanni Sparacino; Enrico Longato (CoRR, 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)

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes. - Davide Dei Cas; Barbara Di Camillo; Gian Paolo Fadini; Giovanni Sparacino; Enrico Longato (Comput. Methods Programs Biomed., 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)

Autoencoder-Based Detection of Insulin Pump Faults in Type 1 Diabetes Treatment. - Elena Idi; Francesco Prendin; 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)