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Citation(s)

  •   Facchinetti A, Del Favero S, Sparacino G, Cobelli C
    An online failure detection method of the glucose sensor-insulin pump system: improved overnight safety of type-1 diabetic subjects. IEEE Trans Biomed Eng. 2013 Feb;60(2):406-16. doi: 10.1109/TBME.2012.2227256. Epub 2012 Nov 15.
  •   Meneghetti L, Dassau E, Doyle FJ 3rd, Del Favero S
    Machine Learning-Based Anomaly Detection Algorithms to Alert Patients Using Sensor Augmented Pump of Infusion Site Failures. J Diabetes Sci Technol. 2022 May;16(3):641-648. doi: 10.1177/1932296821997854. Epub 2021 Mar 9.
  •   Meneghetti L, Facchinetti A, Favero SD
    Model-Based Detection and Classification of Insulin Pump Faults and Missed Meal Announcements in Artificial Pancreas Systems for Type 1 Diabetes Therapy. IEEE Trans Biomed Eng. 2021 Jan;68(1):170-180. doi: 10.1109/TBME.2020.3004270. Epub 2020 Dec 21.
  •   Meneghetti L, Susto GA, Del Favero S
    Detection of Insulin Pump Malfunctioning to Improve Safety in Artificial Pancreas Using Unsupervised Algorithms. J Diabetes Sci Technol. 2019 Nov;13(6):1065-1076. doi: 10.1177/1932296819881452. Epub 2019 Oct 14.

Pilot Study for the Evaluation of Algorithms for the Detection of Subcutaneous Insulin Pump Malfunctions in Subjects With Type 1 Diabetes

Details for clinical trial NCT06147583