AIMC Topic: Blood Glucose

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Prediction of Incident Diabetes in the Jackson Heart Study Using High-Dimensional Machine Learning.

PloS one
Statistical models to predict incident diabetes are often based on limited variables. Here we pursued two main goals: 1) investigate the relative performance of a machine learning method such as Random Forests (RF) for detecting incident diabetes in ...

Performance Analysis of Fuzzy-PID Controller for Blood Glucose Regulation in Type-1 Diabetic Patients.

Journal of medical systems
This paper presents Fuzzy-PID (FPID) control scheme for a blood glucose control of type 1 diabetic subjects. A new metaheuristic Cuckoo Search Algorithm (CSA) is utilized to optimize the gains of FPID controller. CSA provides fast convergence and is ...

Temporal changes in plasma markers of oxidative stress following laparoscopic sleeve gastrectomy in subjects with impaired glucose regulation.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery
BACKGROUND: Laparoscopic sleeve gastrectomy (LSG) is an effective treatment for obesity and associated metabolic complications. Obesity and type 2 diabetes are associated with increased oxidative stress. Previous studies have examined changes in plas...

Acceptability of Robot Assistant in Management of Type 1 Diabetes in Children.

Diabetes technology & therapeutics
BACKGROUND: To find out whether children with type 1 diabetes accept a humanoid robot as an assistant in their diabetes management. In particular, the study aims to determine how the patients feel the robot may contribute to their care and how they r...

Model-Free Machine Learning in Biomedicine: Feasibility Study in Type 1 Diabetes.

PloS one
Although reinforcement learning (RL) is suitable for highly uncertain systems, the applicability of this class of algorithms to medical treatment may be limited by the patient variability which dictates individualised tuning for their usually multipl...

Non-invasive hypoglycemia monitoring system using extreme learning machine for Type 1 diabetes.

ISA transactions
Hypoglycemia is a very common in type 1 diabetic persons and can occur at any age. It is always threatening to the well-being of patients with Type 1 diabetes mellitus (T1DM) since hypoglycemia leads to seizures or loss of consciousness and the possi...

Serum 25-hydroxyvitamin D and metabolic syndrome in a Japanese working population: The Furukawa Nutrition and Health Study.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVE: Increasing evidence has suggested a protective role of vitamin D on metabolic syndrome (MetS). However, studies addressing this issue are limited in Asia and it remains unclear whether calcium could modify the association. We examined the ...

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PloS one
BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took acco...

Multiple Linear Regression and Artificial Neural Network to Predict Blood Glucose in Overweight Patients.

Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association
BACKGROUND: Overweight individuals are at higher risk for developing type II diabetes than the general population. We conducted this study to analyze the correlation between blood glucose and biochemical parameters, and developed a blood glucose pred...