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2020 – today
- 2024
[j16]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)- [j15]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) - [j14]Alessandro Guazzo, Michele Atzeni, Elena Idi, Isotta Trescato, Erica Tavazzi, Enrico Longato, Umberto Manera, Adriano Chiò, Marta Gromicho, Inês Alves, Mamede de Carvalho, Martina Vettoretti, Barbara Di Camillo:
Predicting clinical events characterizing the progression of amyotrophic lateral sclerosis via machine learning approaches using routine visits data: a feasibility study. BMC Medical Informatics Decis. Mak. 24(1): 318 (2024) - [c23]Giovanni Birolo, Pietro Bosoni, Guglielmo Faggioli, Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Alessandro Guazzo, Enrico Longato, Sara C. Madeira, Umberto Manera, Stefano Marchesin, Laura Menotti, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro:
Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2024. CLEF (2) 2024: 118-139 - [c22]Giovanni Birolo, Pietro Bosoni, Guglielmo Faggioli, Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Alessandro Guazzo, Enrico Longato, Sara C. Madeira, Umberto Manera, Stefano Marchesin, Laura Menotti, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro:
Overview of iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. CLEF (Working Notes) 2024: 1312-1331 - [c21]Elena Marinello, Alessandro Guazzo, Enrico Longato, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo:
Using Wearable and Environmental Data to Improve the Prediction of Amyotrophic Lateral Sclerosis and Multiple Sclerosis Progression: an Explorative Study. CLEF (Working Notes) 2024: 1353-1365 - [c20]Luca Cossu, Martina Vettoretti, Giacomo Cappon:
Optimizing Remote Health Monitoring for Digital Platforms: Evaluating the Efficacy of Gamification in Enhancing Data Collection. MIE 2024: 442-446 - [i1]Elena Marinello, Erica Tavazzi, Enrico Longato, Pietro Bosoni, Arianna Dagliati, Mahin Vazifehdan, Riccardo Bellazzi, Isotta Trescato, Alessandro Guazzo, Martina Vettoretti, Eleonora Tavazzi, Lara Ahmad, Roberto Bergamaschi, Paola Cavalla, Umberto Manera, Adriano Chiò, Barbara Di Camillo:
Exploring the Impact of Environmental Pollutants on Multiple Sclerosis Progression. CoRR abs/2408.17376 (2024) - 2023
- [j13]Erica Tavazzi, Enrico Longato, Martina Vettoretti, Helena Aidos, Isotta Trescato, Chiara Roversi, Andreia S. Martins, Eduardo N. Castanho, Ruben Branco, Diogo F. Soares, Alessandro Guazzo, Giovanni Birolo, Daniele Pala, Pietro Bosoni, Adriano Chiò, Umberto Manera, Mamede de Carvalho, Bruno Miranda, Marta Gromicho, Inês Alves, Riccardo Bellazzi, Arianna Dagliati, Piero Fariselli, Sara C. Madeira, Barbara Di Camillo:
Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review. Artif. Intell. Medicine 142: 102588 (2023) - [j12]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) - [j11]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) - [j10]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) - [c19]Guglielmo Faggioli, Alessandro Guazzo, Stefano Marchesin, Laura Menotti, Isotta Trescato, Helena Aidos, Roberto Bergamaschi, Giovanni Birolo, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Enrico Longato, Sara C. Madeira, Umberto Manera, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro:
Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2023. CLEF 2023: 343-369 - [c18]Guglielmo Faggioli, Alessandro Guazzo, Stefano Marchesin, Laura Menotti, Isotta Trescato, Helena Aidos, Roberto Bergamaschi, Giovanni Birolo, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Enrico Longato, Sara C. Madeira, Umberto Manera, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro:
Overview of iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge. CLEF (Working Notes) 2023: 1123-1164 - [c17]Alessandro Guazzo, Isotta Trescato, Enrico Longato, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo:
Baseline Machine Learning Approaches To Predict Multiple Sclerosis Disease Progression. CLEF (Working Notes) 2023: 1219-1232 - [d1]Guglielmo Faggioli, Alessandro Guazzo, Stefano Marchesin, Laura Menotti, Isotta Trescato, Helena Aidos, Roberto Bergamaschi, Giovanni Birolo, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Enrico Longato, Sara C. Madeira, Umberto Manera, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro:
iDPP@CLEF 2023 - Participants' repositories for the Intelligent Disease Prediction Progression Challenge. Zenodo, 2023
- 2022
- [j9]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) - [c16]Alessandro Guazzo, Isotta Trescato, Enrico Longato, Enidia Hazizaj, Dennis Dosso, Guglielmo Faggioli, Giorgio Maria Di Nunzio, Gianmaria Silvello, Martina Vettoretti, Erica Tavazzi, Chiara Roversi, Piero Fariselli, Sara C. Madeira, Mamede de Carvalho, Marta Gromicho, Adriano Chiò, Umberto Manera, Arianna Dagliati, Giovanni Birolo, Helena Aidos, Barbara Di Camillo, Nicola Ferro:
Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2022. CLEF 2022: 395-422 - [c15]Alessandro Guazzo, Isotta Trescato, Enrico Longato, Enidia Hazizaj, Dennis Dosso, Guglielmo Faggioli, Giorgio Maria Di Nunzio, Gianmaria Silvello, Martina Vettoretti, Erica Tavazzi, Chiara Roversi, Piero Fariselli, Sara C. Madeira, Mamede de Carvalho, Marta Gromicho, Adriano Chiò, Umberto Manera, Arianna Dagliati, Giovanni Birolo, Helena Aidos, Barbara Di Camillo, Nicola Ferro:
Overview of iDPP@CLEF 2022: The Intelligent Disease Progression Prediction Challenge. CLEF (Working Notes) 2022: 1130-1210 - [c14]Isotta Trescato, Alessandro Guazzo, Enrico Longato, Enidia Hazizaj, Chiara Roversi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo:
Baseline Machine Learning Approaches To Predict Amyotrophic Lateral Sclerosis Disease Progression. CLEF (Working Notes) 2022: 1277-1293 - [e1]Davide Chicco, Angelo M. Facchiano, Erica Tavazzi, Enrico Longato, Martina Vettoretti, Anna Bernasconi, Simone Avesani, Paolo Cazzaniga:
Computational Intelligence Methods for Bioinformatics and Biostatistics - 17th International Meeting, CIBB 2021, Virtual Event, November 15-17, 2021, Revised Selected Papers. Lecture Notes in Computer Science 13483, Springer 2022, ISBN 978-3-031-20836-2 [contents] - 2021
- [j8]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) - [j7]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) - [c13]Chiara Roversi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo:
A Dynamic Bayesian Network model for simulating the progression to diabetes onset in the ageing population. BHI 2021: 1-4 - [c12]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 - [c11]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 - [c10]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
- [j6]Enrico Longato, Martina Vettoretti, Barbara Di Camillo:
A practical perspective on the concordance index for the evaluation and selection of prognostic time-to-event models. J. Biomed. Informatics 108: 103496 (2020) - [j5]Martina Vettoretti, Giacomo Cappon, Andrea Facchinetti, Giovanni Sparacino:
Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors. Sensors 20(14): 3870 (2020)
2010 – 2019
- 2019
- [j4]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) - [c9]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 - [c8]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 - 2018
- [j3]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) - [j2]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) - [c7]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 - [c6]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 - [c5]Michele Schiavon, Giada Acciaroli, Martina Vettoretti, Alberto Giaretta, Roberto Visentin:
A Model of Acetaminophen Pharmacokinetics and its Effect on Continuous Glucose Monitoring Sensor Measurements. EMBC 2018: 159-162 - [c4]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
- [c3]Iván Contreras, Josep Vehí, Roberto Visentin, Martina Vettoretti:
A Hybrid Clustering Prediction for Type 1 Diabetes Aid: Towards Decision Support Systems Based upon Scenario Profile Analysis. CHASE 2017: 64-69 - 2016
- [j1]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
- [c2]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 - [c1]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
Coauthor Index
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last updated on 2024-11-07 20:31 CET by the dblp team
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