Background: Thalassemia is characterized by the decrease or absence of the synthesis of one or more globin chains of hemoglobin. Thalassemia is distributed worldwide and is characterized by; regular blood transfusion which is creating alloimmunization to erythrocyte antigens is one of the major complications of regular blood transfusions in thalassemia, particularly in patients who are chronically transfused.Objectives: The aims of this study are to understand the immune system profile as the triggering factor for thalassemia.Methods: Thirty patients aging between one year and four months and twenty two years, twenty two of them were boys and eight were girls. Twenty nine patients, their parents are relative except one and studied in the

      Coronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o

Background: Corona virus disease 2019 (COVID-19) is a communicable disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, leading to an ongoing pandemic.

Aim of study: to review the clinical, lab investigation and imaging techniques, in pediatric age group affected COVID-19 to help medical experts better understand and supply timely diagnosis and treatment.

Subjects and methods: this study is a retrospective descriptive clinical study. The medical records of patients were analyzed. Information’s recorded include demographic data, exposure history, symptoms, signs, laboratory findin

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

<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

Background: coronavirus-19 disease recently emerged as a global pandemic affecting the respiratory system. However, during the course of the illness, the disease can directly or indirectly involve other body organs including the liver.

Objectives: This study aimed to determine the incidence of hepatic involvement and its clinical significance in COVID-19 patients.

Patients and Methods: This cross-sectional single-center study was conducted on 112 patients who have an infection with Covid 19 (proved by polymerase chain reaction). Depending on infection severity, patients were categorized into three groups (according to the guidelines of the Chinese National Health Committee)

Since its discovery in December 2019, corona virus was outbreak worldwide with very rapid rate, so it described by WHO as pandemic. It associated with severe acute respiratory distress syndrome, and can enter to cells through Angiotensin Converting Enzyme 2 (ACE 2) receptor which play an important role as regulator for blood pressure. Hypertension is a potential risk factor for sever acute respiratory syndrome COVID-19, and associated with high mortality rate as shown in many epidemiological studies. Moreover, specific antihypertensive medications that infected patients were receiving are not known; only data about renin-angiotensin-aldosterone system (RAAS) are available.  

Background:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to th