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Type 2 diabetes mellitus(T2DM) has become a major social problem threatening the health of the population; the ability to predict its prevalence can help in prevention and early treatment. Existing prediction methods face difficult discovery of ...

Diabetes mellitus Type 2 (DM2T) is a rapidly expanding metabolic endocrine disorder worldwide. It is caused due to inadequate insulin secretion by pancreatic beta cells as well as development of insulin resistance. This study aimed to investigate ...

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• Phytocompounds of GLAE were identified through LC ESI-MS/MS.
• GLAE showed in vitro antioxidant and α-glucosidase enzyme inhibition activity.
• CD analysis revealed insulin structural stabilization by GLAE.
• Phytocompounds of GLAE ...

Type 2 diabetic patients benefit significantly if the disease is well controlled through behavioral changes, namely adopting a healthy lifestyle. Currently, there is some evidence that technological strategies can help patient self-management. ...

The main goals of this work are to study and compare machine learning algorithms to predict the development of type 2 diabetes mellitus.

Four classification algorithms have been considered, studying and comparing the accuracy of each one to ...

• A novel feature selection that entailed both feature importance and multicollinearity concerns was proposed to identify potential factors for the diagnosis of type 2 diabetes mellitus.
• Compared with the AUC values of classifiers in the ...

Background and Objective:Increasing and compelling evidence has been proved that urinary and dietary metal exposure are underappreciated but potentially modifiable biomarkers for type 2 diabetes mellitus (T2DM). The aims of this study were (1) ...

The natural population-based prediction of type 2 diabetes is costly since it needs a high number of resources. Even though much research has used machine learning algorithms to predict type II diabetes, it could not obtain a sufficient ...

Microbiome is closely related to many major human diseases, but it is generally analyzed by the traditional statistical methods such as principal component analysis, principal coordinate analysis, etc. These methods have shortcomings and do not ...

Saeng-Ji-Hwang-Ko (SJHK) is a traditional Korean medicine formula derived from Donguibogam, a classic medical textbook, published in 1613. It is described as a general treatment for So-gal (wasting-thirst, 消渴) ...

• Network pharmacology and molecular docking showed potential antidiabetic compounds and targets of Saeng-Ji-Hwang-Ko (SJHK).

Type 2 diabetes mellitus (T2DM) is reported to cause widespread changes in brain function, leading to cognitive impairments. Research using resting-state functional magnetic resonance imaging data already aims to understand functional changes in ...

The rapidly increasing incidence of Diabetes Mellitus (DM) has shown that DM is a serious disease that endangered human life in all parts of the world. The late stage of Type-II DM (T2DM) in particular is accompanied by complex ...

• An intelligent diagnosis system can be used to help physicians with diabetes diagnosis, which is time saving and efficient.

Decision support systems (DSS) play an increasingly important role in medical practice. By assisting physicians in making clinical decisions and subsequent recommendations, medical DSS are expected to improve the quality of healthcare. The role of ...

Medical experts indulge in numerous strategies for efficient and predictive measures to model the health status of patients and formulate the patterns that are formed in test results. Most patients would dream of their betterments of their health ...

• Information from electronic health records can be used to help us understand what contributes to the onset of diseases including type 2 diabetes mellitus.

Diabetes is responsible for considerable morbidity, healthcare utilisation and mortality in both developed and developing countries. Currently, methods of treating diabetes are inadequate and costly so prevention ...

Machine learning based predictive models have been used in different areas of everyday life for decades. However, with the recent availability of big data, new ways emerge on how to interpret the decisions of machine learning models. In addition ...

Diabetes mellitus is a metabolic disorder leading to hyperglycemia and organ damage. In 2017, the International Diabetes Federation (IDF) reported that about 425 million people living with diabetes, most of which suffer from type 2 diabetes ...

Heart rate variability (HRV) among other methods can be used to assess diabetic cardiac autonomic neuropathy by cardiac intervals were recorded. However, the amount of error depending on this measurement methodology is unclear. To evaluate the ...

Saudi Arabia has one of the highest prevalence of type 2 diabetes mellitus (T2DM) worldwide. The aim of the current study was to analyze the research productivity in T2DM, specifically to characterize and quantify the research on T2DM. Data were ...

The prevalence of type 2 Diabetes Mellitus (T2DM) has reached critical proportions globally over the past few years. Diabetes can cause devastating personal suffering and its treatment represents a major economic burden for every country around ...

The aim of this study is to analyse associated factors with prevention efforts on diabetes mellitus (DM) type 2 in high school student in Makassar. This study was used observational analytic with cross-sectional study conducted in January-February 2016 ...

High levels of physical activity are paramount in ensuring individuals maintain or improve health outcomes, function and quality of life. However, physical activity continues to be low worldwide and rates of conditions associated with sedentary ...