Andrea Facchinetti
Andrea Facchinetti
Associate Professor, Department of Information Engineering, University of Padova
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Zitiert von
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Glucose concentration can be predicted ahead in time from continuous glucose monitoring sensor time-series
G Sparacino, F Zanderigo, S Corazza, A Maran, A Facchinetti, C Cobelli
IEEE Transactions on biomedical engineering 54 (5), 931-937, 2007
Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring
C Pérez-Gandía, A Facchinetti, G Sparacino, C Cobelli, EJ Gómez, ...
Diabetes technology & therapeutics 12 (1), 81-88, 2010
Continuous glucose monitoring sensors for diabetes management: a review of technologies and applications
G Cappon, M Vettoretti, G Sparacino, A Facchinetti
Diabetes & metabolism journal 43 (4), 383-397, 2019
Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results
B Kovatchev, C Cobelli, E Renard, S Anderson, M Breton, S Patek, ...
Journal of diabetes science and technology 4 (6), 1374-1381, 2010
Wearable continuous glucose monitoring sensors: a revolution in diabetes treatment
G Cappon, G Acciaroli, M Vettoretti, A Facchinetti, G Sparacino
Electronics 6 (3), 65, 2017
2019 Clinical practice guidelines for type 2 diabetes mellitus in Korea
G Cappon, M Vettoretti, G Sparacino, A Facchinetti, MK Kim, SH Ko, ...
Diabetes & metabolism journal 43 (4), 398-406, 2019
Neural network incorporating meal information improves accuracy of short-time prediction of glucose concentration
C Zecchin, A Facchinetti, G Sparacino, G De Nicolao, C Cobelli
IEEE transactions on biomedical engineering 59 (6), 1550-1560, 2012
Continuous glucose monitoring sensors: past, present and future algorithmic challenges
A Facchinetti
Sensors 16 (12), 2093, 2016
Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier
D Bruttomesso, A Farret, S Costa, MC Marescotti, M Vettore, A Avogaro, ...
Journal of diabetes science and technology 3 (5), 1014-1021, 2009
Modeling the glucose sensor error
A Facchinetti, S Del Favero, G Sparacino, JR Castle, WK Ward, C Cobelli
IEEE Transactions on Biomedical Engineering 61 (3), 620-629, 2013
Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms
M Falda, S Toppo, A Pescarolo, E Lavezzo, B Di Camillo, A Facchinetti, ...
BMC bioinformatics 13, 1-9, 2012
Enhancing the accuracy of subcutaneous glucose sensors: a real-time deconvolution-based approach
S Guerra, A Facchinetti, G Sparacino, G De Nicolao, C Cobelli
IEEE Transactions on Biomedical Engineering 59 (6), 1658-1669, 2012
Calibration of minimally invasive continuous glucose monitoring sensors: state-of-the-art and current perspectives
G Acciaroli, M Vettoretti, A Facchinetti, G Sparacino
Biosensors 8 (1), 24, 2018
Real-time improvement of continuous glucose monitoring accuracy: the smart sensor concept
A Facchinetti, G Sparacino, S Guerra, YM Luijf, JH DeVries, JK Mader, ...
Diabetes care 36 (4), 793-800, 2013
“Smart” continuous glucose monitoring sensors: on-line signal processing issues
G Sparacino, A Facchinetti, C Cobelli
Sensors 10 (7), 6751-6772, 2010
Continuous glucose monitoring time series and hypo/hyperglycemia prevention: requirements, methods, open problems
G Sparacino, A Facchinetti, A Maran, C Cobelli
Current diabetes reviews 4 (3), 181-192, 2008
Jump neural network for online short-time prediction of blood glucose from continuous monitoring sensors and meal information
C Zecchin, A Facchinetti, G Sparacino, C Cobelli
Computer methods and programs in biomedicine 113 (1), 144-152, 2014
Continuous glucose monitoring in very preterm infants: a randomized controlled trial
A Galderisi, A Facchinetti, GM Steil, P Ortiz-Rubio, F Cavallin, ...
Pediatrics 140 (4), 2017
Characterizing multisegment foot kinematics during gait in diabetic foot patients
Z Sawacha, G Cristoferi, G Guarneri, S Corazza, G Donà, P Denti, ...
Journal of NeuroEngineering and Rehabilitation 6, 1-11, 2009
Model of glucose sensor error components: identification and assessment for new Dexcom G4 generation devices
A Facchinetti, S Del Favero, G Sparacino, C Cobelli
Medical & biological engineering & computing 53, 1259-1269, 2015
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