Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

Background: A number of different types of fluid may accumulate in the pleural space, the most common being transudate, exudate (thin or thick), blood and chyle. All types of pleural effusion are radio graphically identical, though historical, clinical and other radiological features may help limit the diagnostic possibilities. Sometimes, also CT and MRI can help to specify the diagnosis.
Objective: To determine the accuracy of computed tomography (CT) in enabling differentiation of pleural exudates from transudates.
Patients and methods: forty three consecutive patients (43 effusions) underwent contrast-enhanced CT. Thoracocentesis was performed to measure pleural and serum total protein values. Effusions were classified as exudat

The subject matter of the article Prediction of COVID-19 disease and infection rate based on a pre-trained model that supports deep learning. The goal is to build a system to diagnose people as infected or not with covid disease with the percentage of infection and the affected site and to present it with interactive interfaces to facilitate the use of the system for anyone not specialized in the software field. The task is to detect or predict the Coronavirus that affects the airways, lungs, and breathing. It is the cause of many deaths and is still in the process of transformation and development, but with less media exposure. From this standpoint, a medical system was proposed to detect the presence of the Coronavirus in the lung based o

The typical test for diagnosis of severe acute respiratory syndrome coronavirus 2 is a reverse transcription-polymerase chain reaction (RT-PCR) technique, but the chest CT scan might play a complementary role at the first detection of Coronavirus Disease 2019 (COVID-19) pneumonia. Objectives: To determine the sensitivity of CT scan on patients with COVID-19 in Al-Najaf, Iraq, and to compare the accuracy of CT scan with that of RT-PCR technique. Material and Method: This is a prospective study. The patients suspicious of having COVID-19 infection and respiratory symptoms were registered. All patients were diagnosed by RT-PCR and chest CT. Diagnostic performance of CT was intended using RT-PCR as the reference sta

<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

SUMMARY. The objectives of the present study were to assess the possible predictors of COVID-19 severity and duration of hospitalization and to identify the possible correlation between patient parameters, disease severity and duration of hospitalization. The study included retrospective medical record extraction of previous coron avirus COVID-19 patients in Basra hospitals, Iraq from March 1st and May 31st, 2020. The information of the participants was investigated anonymously. All the patients’ characteristics, treatments, vital signs and laboratory tests (hematological, renal and liver function tests) were collected. The analysis was conducted using the SPSS (version 22, USA). Spearman correlation was used to measure the relations

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)

    Coronavirus disease 2019 (COVID-19) is a systemic disease with a substantial impact on the hematopoietic system and hemostasis. Neutrophilia is an early indicator of SARS-CoV-2 infection, while lymphopenia acts as a biomarker of the severity of infection, and the neutrophil-to-lymphocyte ratio (NLR) is the main indicator of cytokine storms. Thus, this study aimed to provide local data about hematological parameters among COVID-19 patients and estimate their correlation with viral load and other factors in severe cases. A total of 99 nasopharyngeal swabs and whole blood specimens were collected from individuals suspected with COVID-19 between October and December 2020. Samples were tested by real time reverse transcript