2 results match your criteria: "and the Sansum Diabetes Research Institute[Affiliation]"
Six-Month Randomized, Multicenter Trial of Closed-Loop Control in Type 1 Diabetes.
N Engl J Med
October 2019
From the University of Virginia Center for Diabetes Technology, Charlottesville (S.A.B., B.P.K., S.M.A.); the Jaeb Center for Health Research, Tampa, FL (D.R., J.W.L., C.K., R.W.B.); the Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford (B.A.B., L.E.), and the Sansum Diabetes Research Institute, Santa Barbara (J.E.P., M.C.) - both in California; the Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN (Y.C.K., V.D.); the Research Division, Joslin Diabetes Center and Department of Pediatrics, Harvard Medical School, Boston (L.M.L., E.I.), and the Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge (E.D., F.J.D.) - both in Massachusetts; the Division of Endocrinology, Icahn School of Medicine at Mount Sinai, New York (C.J.L., D.W.L.); and the Barbara Davis Center for Diabetes, University of Colorado, Anschutz Medical Campus, Aurora (R.P.W., G.P.F.).
Background: Closed-loop systems that automate insulin delivery may improve glycemic outcomes in patients with type 1 diabetes.
Methods: In this 6-month randomized, multicenter trial, patients with type 1 diabetes were assigned in a 2:1 ratio to receive treatment with a closed-loop system (closed-loop group) or a sensor-augmented pump (control group). The primary outcome was the percentage of time that the blood glucose level was within the target range of 70 to 180 mg per deciliter (3.
Design of an Artificial Pancreas using Zone Model Predictive Control with a Moving Horizon State Estimator.
Proc IEEE Conf Decis Control
December 2014
University of California, Santa Barbara, CA, USA, and the Sansum Diabetes Research Institute, Santa Barbara, CA, USA.
A zone model predictive control (zone-MPC) algorithm that utilizes the Moving Horizon State Estimator (MHSE) is presented. The control application is an artificial pancreas for treating people with type 1 diabetes mellitus. During the meal challenge, the prediction quality of the zone-MPC algorithm with the MHSE was significantly better than when using the current Luenberger observer to provide the state estimate.
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