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Items: 1 to 50 of 127

1.

Dynamic changes of Receptor activator of nuclear factor-κB expression in Circulating Tumor Cells during Denosumab predict treatment effectiveness in Metastatic Breast Cancer.

Pantano F, Rossi E, Iuliani M, Facchinetti A, Simonetti S, Ribelli G, Zoccoli A, Vincenzi B, Tonini G, Zamarchi R, Santini D.

Sci Rep. 2020 Jan 28;10(1):1288. doi: 10.1038/s41598-020-58339-2.

2.

A Bayesian Framework to Identify Type 1 Diabetes Physiological Models Using Easily Accessible Patient Data.

Cappon G, Facchinetti A, Sparacino G, Favero SD.

Conf Proc IEEE Eng Med Biol Soc. 2019 Jul;2019:6914-6917. doi: 10.1109/EMBC.2019.8856846.

PMID:
31947429
3.

In-silico Assessment of Preventive Hypotreatment Efficacy and Development of a Continuous Glucose Monitoring Based Algorithm to Prevent/Mitigate Hypoglycemia in Type 1 Diabetes.

Camerlingo N, Vettoretti M, Del Favero S, Cappon G, Sparacino G, Facchinetti A.

Conf Proc IEEE Eng Med Biol Soc. 2019 Jul;2019:4133-4136. doi: 10.1109/EMBC.2019.8857268.

PMID:
31946780
4.

Modeling the error of factory-calibrated continuous glucose monitoring sensors: application to Dexcom G6 sensor data.

Vettoretti M, Favero SD, Sparacino G, Facchinetti A.

Conf Proc IEEE Eng Med Biol Soc. 2019 Jul;2019:750-753. doi: 10.1109/EMBC.2019.8856790.

PMID:
31946005
5.

Development of an Error Model for a Factory-Calibrated Continuous Glucose Monitoring Sensor with 10-Day Lifetime.

Vettoretti M, Battocchio C, Sparacino G, Facchinetti A.

Sensors (Basel). 2019 Dec 3;19(23). pii: E5320. doi: 10.3390/s19235320.

6.

Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device.

Acciaroli G, Zanon M, Facchinetti A, Caduff A, Sparacino G.

Sensors (Basel). 2019 Aug 24;19(17). pii: E3677. doi: 10.3390/s19173677.

7.

Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications.

Cappon G, Vettoretti M, Sparacino G, Facchinetti A.

Diabetes Metab J. 2019 Aug;43(4):383-397. doi: 10.4093/dmj.2019.0121. Review.

8.

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.

Fico G, Hernanzez L, Cancela J, Dagliati A, Sacchi L, Martinez-Millana A, Posada J, Manero L, Verdú J, Facchinetti A, Ottaviano M, Zarkogianni K, Nikita K, Groop L, Gabriel-Sanchez R, Chiovato L, Traver V, Merino-Torres JF, Cobelli C, Bellazzi R, Arredondo MT.

BMC Med Inform Decis Mak. 2019 Aug 16;19(1):163. doi: 10.1186/s12911-019-0887-8.

9.

A Real-Time Continuous Glucose Monitoring-Based Algorithm to Trigger Hypotreatments to Prevent/Mitigate Hypoglycemic Events.

Camerlingo N, Vettoretti M, Del Favero S, Cappon G, Sparacino G, Facchinetti A.

Diabetes Technol Ther. 2019 Nov;21(11):644-655. doi: 10.1089/dia.2019.0139. Epub 2019 Jul 25.

PMID:
31335191
10.

Classification of Postprandial Glycemic Status with Application to Insulin Dosing in Type 1 Diabetes-An In Silico Proof-of-Concept.

Cappon G, Facchinetti A, Sparacino G, Georgiou P, Herrero P.

Sensors (Basel). 2019 Jul 18;19(14). pii: E3168. doi: 10.3390/s19143168.

11.

Simple Linear Support Vector Machine Classifier Can Distinguish Impaired Glucose Tolerance Versus Type 2 Diabetes Using a Reduced Set of CGM-Based Glycemic Variability Indices.

Longato E, Acciaroli G, Facchinetti A, Maran A, Sparacino G.

J Diabetes Sci Technol. 2019 Mar 31:1932296819838856. doi: 10.1177/1932296819838856. [Epub ahead of print]

PMID:
30931604
12.

Combining continuous glucose monitoring and insulin pumps to automatically tune the basal insulin infusion in diabetes therapy: a review.

Vettoretti M, Facchinetti A.

Biomed Eng Online. 2019 Mar 29;18(1):37. doi: 10.1186/s12938-019-0658-x. Review.

13.

Continuous Glucose Monitoring Linked to an Artificial Intelligence Risk Index: Early Footprints of Intraventricular Hemorrhage in Preterm Neonates.

Galderisi A, Zammataro L, Losiouk E, Lanzola G, Kraemer K, Facchinetti A, Galeazzo B, Favero V, Baraldi E, Cobelli C, Trevisanuto D, Steil GM.

Diabetes Technol Ther. 2019 Mar;21(3):146-153. doi: 10.1089/dia.2018.0383.

PMID:
30835533
14.

Detection and Prognostic Relevance of Circulating and Disseminated Tumour Cell in Dogs with Metastatic Mammary Carcinoma: A Pilot Study.

Marconato L, Facchinetti A, Zanardello C, Rossi E, Vidotto R, Capello K, Melchiotti E, Laganga P, Zamarchi R, Vascellari M.

Cancers (Basel). 2019 Feb 1;11(2). pii: E163. doi: 10.3390/cancers11020163.

15.

Single tube liquid biopsy for advanced non-small cell lung cancer.

de Wit S, Rossi E, Weber S, Tamminga M, Manicone M, Swennenhuis JF, Groothuis-Oudshoorn CGM, Vidotto R, Facchinetti A, Zeune LL, Schuuring E, Zamarchi R, Hiltermann TJN, Speicher MR, Heitzer E, Terstappen LWMM, Groen HJM.

Int J Cancer. 2019 Jun 15;144(12):3127-3137. doi: 10.1002/ijc.32056. Epub 2019 Jan 28.

PMID:
30536653
16.

Importance of Recalibrating Models for Type 2 Diabetes Onset Prediction: Application of the Diabetes Population Risk Tool on the Health and Retirement Study.

Vettoretti M, Longato E, Camillo BD, Facchinetti A.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:5358-5361. doi: 10.1109/EMBC.2018.8513554.

PMID:
30441547
17.

Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models.

Acciaroli G, Facchinetti A, Pillonetto G, Sparacino G.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:3630-3633. doi: 10.1109/EMBC.2018.8512944.

PMID:
30441162
18.

Bayesian Model Selection Framework to Improve Calibration of Continuous Glucose Monitoring Sensors for Diabetes Management.

Acciaroli G, Vettoretti M, Facchinetti A, And Sparacino G.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:29-32. doi: 10.1109/EMBC.2018.8512240.

PMID:
30440333
19.

Optimal Insulin Bolus Dosing in Type 1 Diabetes Management: Neural Network Approach Exploiting CGM Sensor Information.

Cappon G, Vettoretti M, Marturano F, Facchinetti A, Sparacino G.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:1-4. doi: 10.1109/EMBC.2018.8512250.

PMID:
30440244
20.

Clonal heterogeneity of melanoma in a paradigmatic case study: future prospects for circulating melanoma cells.

Scaini MC, Pigozzo J, Pizzi M, Manicone M, Chiarion-Sileni V, Zambenedetti P, Rugge M, Zanovello P, Rossi E, Zamarchi R, Facchinetti A.

Melanoma Res. 2019 Feb;29(1):89-94. doi: 10.1097/CMR.0000000000000510.

PMID:
30222690
21.

Prediction of Adverse Glycemic Events From Continuous Glucose Monitoring Signal.

Gadaleta M, Facchinetti A, Grisan E, Rossi M.

IEEE J Biomed Health Inform. 2019 Mar;23(2):650-659. doi: 10.1109/JBHI.2018.2823763. Epub 2018 Apr 6.

PMID:
29993992
22.

In Silico Assessment of Literature Insulin Bolus Calculation Methods Accounting for Glucose Rate of Change.

Cappon G, Marturano F, Vettoretti M, Facchinetti A, Sparacino G.

J Diabetes Sci Technol. 2019 Jan;13(1):103-110. doi: 10.1177/1932296818777524. Epub 2018 May 31.

23.

Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications.

Vettoretti M, Cappon G, Acciaroli G, Facchinetti A, Sparacino G.

J Diabetes Sci Technol. 2018 Sep;12(5):1064-1071. doi: 10.1177/1932296818774078. Epub 2018 May 22.

24.

Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data.

Longato E, Acciaroli G, Facchinetti A, Hakaste L, Tuomi T, Maran A, Sparacino G.

Comput Biol Med. 2018 May 1;96:141-146. doi: 10.1016/j.compbiomed.2018.03.007. Epub 2018 Mar 14.

PMID:
29573667
25.

Calibration of Minimally Invasive Continuous Glucose Monitoring Sensors: State-of-The-Art and Current Perspectives.

Acciaroli G, Vettoretti M, Facchinetti A, Sparacino G.

Biosensors (Basel). 2018 Mar 13;8(1). pii: E24. doi: 10.3390/bios8010024. Review.

26.

Head-to-head comparison of the accuracy of Abbott FreeStyle Libre and Dexcom G5 mobile.

Boscari F, Galasso S, Acciaroli G, Facchinetti A, Marescotti MC, Avogaro A, Bruttomesso D.

Nutr Metab Cardiovasc Dis. 2018 Apr;28(4):425-427. doi: 10.1016/j.numecd.2018.01.003. Epub 2018 Jan 31. No abstract available.

PMID:
29502924
27.

A Neural-Network-Based Approach to Personalize Insulin Bolus Calculation Using Continuous Glucose Monitoring.

Cappon G, Vettoretti M, Marturano F, Facchinetti A, Sparacino G.

J Diabetes Sci Technol. 2018 Mar;12(2):265-272. doi: 10.1177/1932296818759558.

28.

HAPT2D: high accuracy of prediction of T2D with a model combining basic and advanced data depending on availability.

Di Camillo B, Hakaste L, Sambo F, Gabriel R, Kravic J, Isomaa B, Tuomilehto J, Alonso M, Longato E, Facchinetti A, Groop LC, Cobelli C, Tuomi T.

Eur J Endocrinol. 2018 Apr;178(4):331-341. doi: 10.1530/EJE-17-0921. Epub 2018 Jan 25.

PMID:
29371336
29.

Yet Another Glucose Variability Index: Time for a Paradigm Change?

Cobelli C, Facchinetti A.

Diabetes Technol Ther. 2018 Jan;20(1):1-3. doi: 10.1089/dia.2017.0397. No abstract available.

PMID:
29320256
30.

Toward Calibration-Free Continuous Glucose Monitoring Sensors: Bayesian Calibration Approach Applied to Next-Generation Dexcom Technology.

Acciaroli G, Vettoretti M, Facchinetti A, Sparacino G.

Diabetes Technol Ther. 2018 Jan;20(1):59-67. doi: 10.1089/dia.2017.0297. Epub 2017 Dec 21.

PMID:
29265916
31.

FreeStyle Libre and Dexcom G4 Platinum sensors: Accuracy comparisons during two weeks of home use and use during experimentally induced glucose excursions.

Boscari F, Galasso S, Facchinetti A, Marescotti MC, Vallone V, Amato AML, Avogaro A, Bruttomesso D.

Nutr Metab Cardiovasc Dis. 2018 Feb;28(2):180-186. doi: 10.1016/j.numecd.2017.10.023. Epub 2017 Nov 11.

PMID:
29258716
32.

Liquid biopsy for monitoring anaplastic lymphoma kinase inhibitors in non-small cell lung cancer: two cases compared.

Manicone M, Scaini MC, Rodriquenz MG, Facchinetti A, Tartarone A, Aieta M, Zamarchi R, Rossi E.

J Thorac Dis. 2017 Oct;9(Suppl 13):S1391-S1396. doi: 10.21037/jtd.2017.08.151. Review.

33.

Critical issues in the clinical application of liquid biopsy in non-small cell lung cancer.

Manicone M, Poggiana C, Facchinetti A, Zamarchi R.

J Thorac Dis. 2017 Oct;9(Suppl 13):S1346-S1358. doi: 10.21037/jtd.2017.07.28. Review.

34.

Continuous Glucose Monitoring in Very Preterm Infants: A Randomized Controlled Trial.

Galderisi A, Facchinetti A, Steil GM, Ortiz-Rubio P, Cavallin F, Tamborlane WV, Baraldi E, Cobelli C, Trevisanuto D.

Pediatrics. 2017 Oct;140(4). pii: e20171162. doi: 10.1542/peds.2017-1162. Epub 2017 Sep 15.

35.

Type-1 Diabetes Patient Decision Simulator for In Silico Testing Safety and Effectiveness of Insulin Treatments.

Vettoretti M, Facchinetti A, Sparacino G, Cobelli C.

IEEE Trans Biomed Eng. 2018 Jun;65(6):1281-1290. doi: 10.1109/TBME.2017.2746340. Epub 2017 Aug 29.

PMID:
28866479
36.

Expected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin.

Longato E, Garrido M, Saccardo D, Montesinos Guevara C, Mani AR, Bolognesi M, Amodio P, Facchinetti A, Sparacino G, Montagnese S.

PLoS One. 2017 Jun 30;12(6):e0180315. doi: 10.1371/journal.pone.0180315. eCollection 2017.

37.

Exploring the Frequency Domain of Continuous Glucose Monitoring Signals to Improve Characterization of Glucose Variability and of Diabetic Profiles.

Fico G, Hernández L, Cancela J, Isabel MM, Facchinetti A, Fabris C, Gabriel R, Cobelli C, Arredondo Waldmeyer MT.

J Diabetes Sci Technol. 2017 Jul;11(4):773-779. doi: 10.1177/1932296816685717. Epub 2017 Jan 9.

38.

Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.

Biagi L, Ramkissoon CM, Facchinetti A, Leal Y, Vehi J.

Sensors (Basel). 2017 Jun 12;17(6). pii: E1361. doi: 10.3390/s17061361.

39.

Diabetes and Prediabetes Classification Using Glycemic Variability Indices From Continuous Glucose Monitoring Data.

Acciaroli G, Sparacino G, Hakaste L, Facchinetti A, Di Nunzio GM, Palombit A, Tuomi T, Gabriel R, Aranda J, Vega S, Cobelli C.

J Diabetes Sci Technol. 2018 Jan;12(1):105-113. doi: 10.1177/1932296817710478. Epub 2017 Jun 1.

40.

Reduction of Blood Glucose Measurements to Calibrate Subcutaneous Glucose Sensors: A Bayesian Multiday Framework.

Acciaroli G, Vettoretti M, Facchinetti A, Sparacino G, Cobelli C.

IEEE Trans Biomed Eng. 2018 Mar;65(3):587-595. doi: 10.1109/TBME.2017.2706974. Epub 2017 May 23.

PMID:
28541194
41.

A Model of Self-Monitoring Blood Glucose Measurement Error.

Vettoretti M, Facchinetti A, Sparacino G, Cobelli C.

J Diabetes Sci Technol. 2017 Jul;11(4):724-735. doi: 10.1177/1932296817698498. Epub 2017 Mar 16.

42.

Retrofitting Real-Life Dexcom G5 Data.

Favero SD, Facchinetti A, Sparacino G, Cobelli C.

Diabetes Technol Ther. 2017 Apr;19(4):237-245. doi: 10.1089/dia.2016.0413. Epub 2017 Mar 13.

PMID:
28287834
43.

Continuous Glucose Monitoring Sensors: Past, Present and Future Algorithmic Challenges.

Facchinetti A.

Sensors (Basel). 2016 Dec 9;16(12). pii: E2093. Review.

44.

Remote Blood Glucose Monitoring in mHealth Scenarios: A Review.

Lanzola G, Losiouk E, Del Favero S, Facchinetti A, Galderisi A, Quaglini S, Magni L, Cobelli C.

Sensors (Basel). 2016 Nov 24;16(12). pii: E1983. Review.

45.

Predicting Insulin Treatment Scenarios with the Net Effect Method: Domain of Validity.

Vettoretti M, Facchinetti A, Sparacino G, Cobelli C.

Diabetes Technol Ther. 2016 Nov;18(11):694-704.

PMID:
27860496
46.

Switching from twice-daily glargine or detemir to once-daily degludec improves glucose control in type 1 diabetes. An observational study.

Galasso S, Facchinetti A, Bonora BM, Mariano V, Boscari F, Cipponeri E, Maran A, Avogaro A, Fadini GP, Bruttomesso D.

Nutr Metab Cardiovasc Dis. 2016 Dec;26(12):1112-1119. doi: 10.1016/j.numecd.2016.08.002. Epub 2016 Aug 6.

PMID:
27618501
47.

From Two to One Per Day Calibration of Dexcom G4 Platinum by a Time-Varying Day-Specific Bayesian Prior.

Acciaroli G, Vettoretti M, Facchinetti A, Sparacino G, Cobelli C.

Diabetes Technol Ther. 2016 Aug;18(8):472-9. doi: 10.1089/dia.2016.0088.

PMID:
27512826
48.

Monitoring and Characterization of Circulating Tumor Cells (CTCs) in a Patient With EML4-ALK-Positive Non-Small Cell Lung Cancer (NSCLC).

Aieta M, Facchinetti A, De Faveri S, Manicone M, Tartarone A, Possidente L, Lerose R, Mambella G, Calderone G, Zamarchi R, Rossi E.

Clin Lung Cancer. 2016 Sep;17(5):e173-e177. doi: 10.1016/j.cllc.2016.05.002. Epub 2016 May 18. No abstract available.

PMID:
27397482
49.

How Much Is Short-Term Glucose Prediction in Type 1 Diabetes Improved by Adding Insulin Delivery and Meal Content Information to CGM Data? A Proof-of-Concept Study.

Zecchin C, Facchinetti A, Sparacino G, Cobelli C.

J Diabetes Sci Technol. 2016 Aug 22;10(5):1149-60. doi: 10.1177/1932296816654161. Print 2016 Sep.

50.

Modeling Transient Disconnections and Compression Artifacts of Continuous Glucose Sensors.

Facchinetti A, Del Favero S, Sparacino G, Cobelli C.

Diabetes Technol Ther. 2016 Apr;18(4):264-72. doi: 10.1089/dia.2015.0250. Epub 2016 Feb 16.

PMID:
26882463

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