AIMC Topic: Blood Glucose Self-Monitoring

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How Knowledge Emerges From Artificial Intelligence Algorithm and Data Visualization for Diabetes Management.

Journal of diabetes science and technology
BACKGROUND: Self-monitoring blood glucose (SMBG) is facilitated by application available to analyze these data. They are mainly based on descriptive statistical analyses. In this study, we are proposing a method inspired by artificial intelligence al...

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 ...

A Dual Mode Adaptive Basal-Bolus Advisor Based on Reinforcement Learning.

IEEE journal of biomedical and health informatics
Self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) are commonly used by type 1 diabetes (T1D) patients to measure glucose concentrations. The proposed adaptive basal-bolus algorithm (ABBA) supports inputs from either SMBG...

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...

Commercial glucometer as signal transducer for simple evaluation of DNA methyltransferase activity and inhibitors screening.

Analytica chimica acta
DNA methyltransferase (MTase) plays an important role in many biological processes and has been recognized as a predictive cancer biomarker far before other signs of malignancy and a therapeutic target in cancer treatment. Thus simple and sensitive d...

Hypoglycemia prediction using machine learning models for patients with type 2 diabetes.

Journal of diabetes science and technology
Minimizing the occurrence of hypoglycemia in patients with type 2 diabetes is a challenging task since these patients typically check only 1 to 2 self-monitored blood glucose (SMBG) readings per day. We trained a probabilistic model using machine lea...

Enhancing Chronic Diabetes Care with Companion Robots in Rural Taiwan.

Studies in health technology and informatics
Managing chronic diabetes in rural Taiwan remains challenging due to limited medical access and low health literacy. This pilot study evaluated a two-month, two-phase intervention using Bluetooth-enabled glucometers, smart wristbands, and a gamified ...