In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in R program by using some existing packages.
Background: Periodontal disease is a chronic bacterial infection that affects the gingiva and bone supporting the teeth. Smoking, which is an important risk factor for periodontitis, induce oxidative stress in the body and cause an imbalance between reactive oxygen species (ROS) and antioxidants, such as superoxide dismutase (SOD). This study aimed to evaluate the influence of smoking on periodontal health status by estimating the levels of salivary SOD level in non-smokers (controls) and light and heavy smokers and to test the correlation between the SOD enzyme level and the clinical periodontal parameters in each group. Materials and Methods: The study sample consisted of 75 male, with age ranged from 35 to 50 years. Clinically, the perio
... Show MoreBackground: Visfatin is a novel adipokine that mainly secreted by visceral adipose tissue, had an important role in inflammation and immune system. Creatine Kinase (CK) which is an enzyme that is involved in energy metabolism, found in large amounts in myocardium, brain and skeletal tissues. This study is carried out To evaluate the periodontal health status of the study groups (chronic periodontitis and chronic periodontitis with coronary atherosclerosis) and control groups, to measure the salivary levels of visfatin and Creatine Kinase in these groups and compare between them, and to determine the correlations between salivary visfatin and Creatine Kinase levels with the periodontal parameters in the three groups. Materials and Methods: e
... Show MoreBackground: Systemic sclerosis (SSc) is a chronic autoimmune illness, which is consider by three main features: Sclerotic changes in the skin and internal organs, Vasculopathy of small blood vessels, Particular autoantibodies (1). The most important autoantibodies appeared significantly in SSc patients are anti-topoisomerase I autoantibody (Scl-70), anti-centromere autoantibody (ACA), and anti-RNA polymerase III autoantibody (RNAP3) (2). Anti-centromere antibodies (ACA) are infrequent in rheumatic conditions and in healthy persons but occur commonly in limited systemic sclerosis (CREST syndrome), and rarely appeared in the diffuse form of systemic sclerosis (3). Anti-Ro/SSA and antiLa/SSB, antibodies directed against Ro/La ribonucleoprot
... Show MoreHealthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
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