“Learning” Can Improve the Blood Glucose Control Performance for Type 1 Diabetes Mellitus-Reference-Cited by-同舟云学术

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“Learning” Can Improve the Blood Glucose Control Performance for Type 1 Diabetes Mellitus

Published:2017-01 Issue:1 Volume:19 Page:41-48
ISSN:1520-9156
Container-title:Diabetes Technology & Therapeutics
language:en
Short-container-title:Diabetes Technology & Therapeutics

Author:

Wang Youqing¹,Zhang Jinping²,Zeng Fanmao¹,Wang Na²,Chen Xiaoping²,Zhang Bo²,Zhao Dong¹,Yang Wenying²,Cobelli Claudio³

Affiliation:

1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China.

2. Department of Endocrinology, China-Japan Friendship Hospital, Beijing, China.

3. Department of Information Engineering, University of Padova, Padova, Italy.

Publisher

Mary Ann Liebert Inc

Subject

Medical Laboratory Technology,Endocrinology,Endocrinology, Diabetes and Metabolism

Link

http://www.liebertpub.com/doi/pdf/10.1089/dia.2016.0328

Reference25 articles.

1. The Effect of Intensive Treatment of Diabetes on the Development and Progression of Long-Term Complications in Insulin-Dependent Diabetes Mellitus

2. Intensive Diabetes Treatment and Cardiovascular Disease in Patients with Type 1 Diabetes

3. Microvascular Complications of Diabetes Mellitus: Renal Protection Accompanies Cardiovascular Protection

4. Feasibility of Outpatient Fully Integrated Closed-Loop Control

5. Feasibility of Automating Insulin Delivery for the Treatment of Type 1 Diabetes

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1. Blood Glucose Prediction from Nutrition Analytics in Type 1 Diabetes: A Review;Nutrients;2024-07-10

2. In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors;Nutrients;2023-09-22

3. Incorporating Sparse and Quantized Carbohydrates Suggestions in Model Predictive Control for Artificial Pancreas in Type 1 Diabetes;IEEE Transactions on Control Systems Technology;2023-03

4. Insulin infusion rate control using information theoretic–based nonlinear model predictive control for type 1 diabetes patients;Transactions of the Institute of Measurement and Control;2022-09-15

5. Incorporating Prior Information in Adaptive Model Predictive Control for Multivariable Artificial Pancreas Systems;Journal of Diabetes Science and Technology;2021-12-03

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