Abstract Depending on their protective properties against different cases of Colorectal Cancer (CRC), vitamins C, D, and E are the main focus of this research. CRC is one of the global public health concerns. 30 healthy individuals provided serum samples, whereas the group of CRC patients was divided into three, totaling 90 individuals. Group I consisted of 30 newly diagnosed cases of CRC. Group II 30 consisted of consisted of 30 CRC patients who were administered three cycles of chemotherapy. Group III consisted of 30 diagnosed CRC patients who also have non-alcoholic fatty liver disease (NAFLD). The concentrations and groups of vitamins C, D, and E were evaluated using ELISA. The levels of Vitamin C were significantly lower (p &l

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Prostate cancer is an important and potentially fatal disease in humans. Both genetic and environmental risk factors are associated with increased risk of prostate cancer among Asian pop

Hashimoto Thyroiditis (HT) is the most common autoimmune thyroid disease and the commonest cause ofhypothyroidism. C-reactive protein (CRP) is synthesized in hepatocyte in response to autoimmune disorders;strongly induced by IL-6. This study aimed to estimate serum IL-6 and CRP levels in autoimmune and non-autoimmune hypothyroidism. The present study included 60 Iraqi female hypothyroid patients divided to 30autoimmune and 30 non-autoimmune, with age ranged between 24-50 years and 30 healthy controls withage ranged between 27-52 years. Serum samples were collected from study groups. The levels of thyroidhormones (TSH, T4 and T3) were determined by using automated Chemiluminescence Immunoassay (CLIA)analysis system. Detection the levels of t