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Blood Glucose Self-Monitoring

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A Group Decision Making Framework Based on Neutrosophic TOPSIS Approach for Smart Medical Device Selection.

Journal of medical systems
Advances in the medical industry has become a major trend because of the new developments in information technologies. This research offers a novel approach for estimating the smart medical devices (SMDs) selection process in a group decision making ...

Glycemic-aware metrics and oversampling techniques for predicting blood glucose levels using machine learning.

PloS one
Techniques using machine learning for short term blood glucose level prediction in patients with Type 1 Diabetes are investigated. This problem is significant for the development of effective artificial pancreas technology so accurate alerts (e.g. hy...

Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.

Journal of the American Medical Informatics Association : JAMIA
We introduce data assimilation as a computational method that uses machine learning to combine data with human knowledge in the form of mechanistic models in order to forecast future states, to impute missing data from the past by smoothing, and to i...

Knowledge-driven dictionaries for sparse representation of continuous glucose monitoring signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Continuous glucose monitoring (CGM) of patients with diabetes allows the effective management of the disease and reduces the risk of hypoglycemic or hyperglycemic episodes. Towards this goal, the development of reliable CGM models is essential for re...

The Promise and Perils of Wearable Physiological Sensors for Diabetes Management.

Journal of diabetes science and technology
Development of truly useful wearable physiologic monitoring devices for use in diabetes management is still in its infancy. From wearable activity monitors such as fitness trackers and smart watches to contact lenses measuring glucose levels in tears...

Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor.

Journal of diabetes science and technology
BACKGROUND: In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabet...

Automatic Adaptation of Basal Insulin Using Sensor-Augmented Pump Therapy.

Journal of diabetes science and technology
BACKGROUND: People with insulin-dependent diabetes rely on an intensified insulin regimen. Despite several guidelines, they are usually impractical and fall short in achieving optimal glycemic outcomes. In this work, a novel technique for automatic a...

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

Journal of diabetes science and technology
BACKGROUND: In type 1 diabetes (T1D) therapy, the calculation of the meal insulin bolus is performed according to a standard formula (SF) exploiting carbohydrate intake, carbohydrate-to-insulin ratio, correction factor, insulin on board, and target g...

Blood glucose level prediction based on support vector regression using mobile platforms.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The correct treatment of diabetes is vital to a patient's health: Staying within defined blood glucose levels prevents dangerous short- and long-term effects on the body. Mobile devices informing patients about their future blood glucose levels could...

A Risk Based Neural Network Approach for Predictive Modeling of Blood Glucose Dynamics.

Studies in health technology and informatics
For type 1 diabetes patients, maintaining the blood glucose (BG) at normal values is a challenging task due to e.g. variable insulin reactions, diets, lifestyles, emotional conditions, etc. Hyperglycemic and hypoglycemic events can generate various c...