Background: Diabetic neuropathy can affect any peripheral nerve, including sensory neurons, motor neurons, and the autonomic nervous system. Therefore, diabetic neuropathy has the potential to affect essentially any organ and can affect parts of the nervous system like the optic nerve, spinal cord, and brain. In addition, chronic hyperglycemia affects Schwann cells, and more severe patterns of diabetic neuropathy in humans involve demyelization. Schwann cell destruction might cause a number of changes in the axon. study aims to evaluate serum myelin protein level as a predicting marker in the diagnosis of diabetic neuropathy and to prevent early neuropathy complications of type 2 diabetes.

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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

The research discusses the most important goals and means of IGAD in making peace in Sudan and then regional peace.

The study aims to identify the degree of implementation of the coronavirus prevention standards (covid-19) in the kingdom of Saudi Arabia and compare it with the families of intellectual disabilities. The study population consisted of all families residing in the Kingdom of Saudi Arabia. To achieve the objectives of the research, the analytical descriptive approach was employed. The study sample consisted of (372) families, among them (84) families with intellectual disabilities, and (288) families without intellectual disabilities. They were chosen from the Saudi community according to what is available for collection in a simple random way, using the standard criteria for the prevention of coronavirus (Covid- 19) Prepared by the resear

The purpose of this research is to find the estimator of the average proportion of defectives based on attribute samples. That have been curtailed either with rejection of a lot finding the kth defective or with acceptance on finding the kth non defective.

The MLE (Maximum likelihood estimator) is derived. And also the ASN in Single Curtailed Sampling has been derived and we obtain a simplified Formula All the Notations needed are explained.

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol