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Big data has been revolutionizing individualized medicine, improving the results of diagnostic imaging, genetic testing, and by providing frameworks for electronic health record sharing and analysis. In this paper we present a nextstep in personalized data-driven health by demonstrating the capability of predictive individualized models to model peak postprandial plasma glucose concentrations. Past...
Controlling blood glucose is a way to avoid complications of diabetes. Blood glucose monitoring is a way to test the concentration of glucose in the blood. This study aims to determine the suitability of Artificial Raindrop Algorithm (ARA) and capacitance method in measuring the blood glucose. ARA is a new search algorithm that produces very promising results on the nonlinear function approximation...
The Rare Sugars exist naturally and have many kinds (more than 50). They have good effect for health such as prevention of increasing the blood‐sugar level after eating, suppression of fat accumulation, suppression of increasing the blood pressure, and anti- oxidative effect etc. It is in the spotlight for many people especially for those who are in the metabolic syndrome. There are few related papers...
Previously, many researches had been done on non-invasive using near-infrared sensing. Sia [1] had investigated near-infrared sensing using signal penetrating finger method. However, by using finger penetration, there are no results obtained. He only obtained signal using glucose concentration. Therefore the objectives of this research are to investigate the performance of three different wavelength...
Effective management of diabetes is crucial for patient wellbeing and the prevention of low blood sugar levels (Hypoglycemia) and high blood sugar levels (Hyperglycemia) both of which can be potentially dangerous. Traditionally log books are maintained by patients to record information such as insulin usage and their meals. The ever increasing popularity of smart phones has resulted in various applications...
This paper presents a control strategy for blood glucose (BG) level regulation in type 1 diabetic patients. To design the controller, model-based predictive control scheme has been applied to a newly developed diabetic patient model. The controller is provided with a feedforward loop to improve meal compensation, a gain-scheduling scheme to account for different BG levels, and an asymmetric cost function...
Hypoglycemia or low blood glucose is a common and serious side effect of insulin therapy in patients with diabetes. Hypoglycemia is unpleasant and can result in unconsciousness, seizures and even death. HypoMon is a realtime non-invasive monitor that measures relevant physiological parameters continuously to provide detection of hypoglycemic episodes in type 1 diabetes mellitus patients (T1DM). Based...
We developed a methodology for constructing scoring systems to support bivalent decision making in clinical medicine. Such systems could be of great benefit in forced-choice decision-making situations as well as in triaging, screening, and diagnostic applications. Our methodology combines medical judgment with explicit computer-derived information to identify an optimum parsimonious set of variables...
Parathyroid Hormone (PTH) is an important biochemical indicator for the medical condition of osteodystrophy in patients on hemodialysis. Prior studies have been conducted to classify hemodialysis patients based on their PTH level, using neural networks. This paper introduces the possibilities of predicting parathyroid hormone levels in the more specific case of diabetic patients. The performance of...
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