This article comprehensively examines the history, diagnosis, genetics, diversity, and treatment of SARS-CoV-2. It details the emergence of coronaviruses over the past 50 years, including the coronavirus from 2019 and its subsequent mutations, along with updated information about this virus. This review explains the development and nomenclature of coronaviruses, their cellular invasion through glycoprotein spikes binding to ACE-2 receptors, and the mechanism of cell entry via endocytosis. Diagnosis methods for COVID-19, including nucleic acid amplification, serology, and imaging techniques like chest X-ray and CT scan tests, are discussed. Treatment approaches for COVID-19 are outlined, emphasizing healthcare, antiviral medications like Rem

Road accidents have been identified as one of the main causes of death and have a significant effect on public health challenges, economic growth and development. The Iraqi transport infrastructure has suffered from the effects of war, carelessness, and lack of investment. As a result, road traffic accidents have increased, and the current efforts to address road safety are minimal in comparison to the growing level of citizen suffering. The objective of this study was to provincially analyze traffic accidents in Iraq using data from 2010 to 2020 to shed light on the current situation. Three key conclusions were made from the results: first, people aged 35 years and under was the age group recorded in the most traffic accidents; second, Al-

Since the appearance of COVID-19 disease as an epidemic and pandemic disease, many studies are performed to uncover the genetic nature of the newly discovered coronavirus with unique clinical features. The last three human coronavirus outbreaks, SARS-CoV, MERS-CoV and SARS-CoV-2 are caused by Beta-Coronaviruses. Horizontal genetic materials transfer was proven from one coronavirus to the other coronavirus of non-human origin like infectious bronchitis virus (IBV) of avian. Horizontal genetic materials transfer was also from non-corona viruses like astroviruses and equine rhinovirus (ERV-2) or from coronavirus-unrelated viruses, like influenza virus type C. However, SARS-CoV-2 is identical to SARS-CoV and MERS-CoV. Interestingly, Wuhan ci

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

Objective: To Evaluate the Roley of Cytotoxic T-Lymphocytek antigen 4 Polymorphism and soluble immune checkpoint level (PD-1,PDL-1 and CTLA-4 ) in SARS-Cov-2 patients. Methods: Fromt October 2020 to April 2021, the currentk study was conducted in Baghdad-Iraq. Ninety patients with Confirmatory SARS-Cov-2 by PCR were inclusion in the study, and they were seeking treatment at Medical City in Baghdad's Teaching Hospital (BTH). Patients with SARS-Cov-2 were divided into two groups: those with Sever SARS-Cov-2 symptom and those with mild - moderate SARS-Cov-2 symptoms (cross sectional study. Patients with another form of autoimmune illness, malignant, diabetes, under the age of 18 and pregnant women were excluded. Results: Data rega

A shocking third species emerged from a family of coronaviruses (CoV) in late 2019 following viruses causing SARS (Severe Acute Respiratory Syndrome-CoV) in 2003 and MERS (Middle East Respiratory Syndrome-CoV) in 2012; it’s a novel coronavirus now called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; formerly called 2019-nCoV). First emerging in China, it has spread rapidly across the globe, giving rise to significant social and economic costs and imposing severe strain on healthcare systems. Since many attempts to control viral spread has been futile, the only old practice of containment including city lockdown and social distancing are working to some extent. Unfortunately, specific antiviral drugs and vaccines remain u

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea