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Go to Editorial ManagerDiabetic peripheral neuropathy represents one of the common long-terms complications that effect about fifty percentage?of diabetes patients. The habitual diagnosis tool based on nerve conduction study that examine the nerve damage and classify the patient status into normal and diabetic peripheral neuropathy with degree of severity without considering the effect on skeletal muscle and take on patient data. A complementary diagnostic tool proposed, in this study integrates the patient’s data including body mass index, age and duration of diabetic, average blood glucose levels, nerve conduction study that involves amplitude and latency of peroneal and tibial nerves and muscle ultrasound alongside the machine learning algorithms to facilitate the clinicians for a precise diagnosis. A group of control and diabetic patients utilized to gather the data with calculating the muscle thickness and statistical properties from the gray-level ultrasound images of six skeletal muscles. Support vector machine, naïve bayes, ensemble of bagged tree and artificial neural network supervised machine learning algorithms categorize each class with a high classification accuracy, 98.1% for tibialis anterior with naïve bayes algorithm. The outcomes of this study show a promising complementary diagnostic tool that will help the clinicians to perform an exact diagnosis and disclose the side effect on both nerves and muscles of diabetic patients.
Diabetes is a long-term medical condition that impacts the way your body converts food into energy, it has the potential to lead to several severe health complications, such as heart disease, stroke, vision impairment, kidney issues, and nerve damage. Nevertheless, individuals with diabetes can lead extended and healthy lives with effective management. The goal of diabetes treatment is to keep your blood sugar levels within a healthy range. So Glucose measurement is an important part of diabetes management. It allows people with diabetes to track their blood sugar levels and make adjustments to their diet and medication as needed. Morning fasting blood glucose typically falls within the range of (70 mg/dL) to (110 mg/dL), while after a meal, blood glucose levels should ideally be below (140 mg/dL). In this proposed work an Arduino-based noninvasive glucose measurement device is proposed. Non-invasive glucose measurement devices do not require the user to prick their finger to draw blood. A Red Laser (RL) technique, is employed, this method surpasses the other invasive approach and non-invasive methods in terms of superiority. Since invasive techniques can be painful and expensive. This paper describes a new way to measure blood sugar levels without having to prick your finger. The method uses a red laser to shine light through the skin and measure how much the light is bent. The amount of bending tells the device how much sugar is in the blood. Numerous tests and experimental outcomes have been produced to demonstrate the exceptional accuracy of the proposed method.
In today's world, Urinary Tract disorders such as obstructions whatever the causes (stricture, stones), are prevalent and can be extremely dangerous and painful for individuals. One of the most important instruments in the Urological sector for a variety of clinical diseases is the Ureteral stent, a minimally invasive surgical tool for relieving blockages and facilitating kidney-to-Bladder drainage. This review addressed the problems of biofilm formation and polymers currently available for use as new biomaterials in new Ureteral stent designs, providing a comprehensive update on recent developments in stent development. It also evaluated the various biomaterials that found application as Ureteral stents in relation to various issues such as encrustation, bacterial colonization, urinary tract infections, and related clinical issues. This study concluded with a discussion of biomaterials' potential applications and the design in the Urinary Tract.