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Hematological changes associated with COVID‐19 infection
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Abstract<sec><title>Background

The unresolved COVID‐19 pandemic considerably impacts the health services in Iraq and worldwide. Consecutive waves of mutated virus increased virus spread and further constrained health systems. Although molecular identification of the virus by polymerase chain reaction is the only recommended method in diagnosing COVID‐19 infection, radiological, biochemical, and hematological studies are substantially important in risk stratification, patient follow‐up, and outcome prediction.

Aim

This narrative review summarized the hematological changes including the blood indices, coagulative indicators, and other associated biochemical laboratory markers in different stages of COVID‐19 infection, highlighting the diagnostic and prognostic significance.

Methods

Literature search was conducted for multiple combinations of different hematological tests and manifestations with novel COVID‐19 using the following key words: “hematological,” “complete blood count,” “lymphopenia,” “blood indices,” “markers” "platelet" OR "thrombocytopenia" AND "COVID‐19," "coronavirus2019," "2019‐nCoV," OR "SARS‐CoV‐2." Articles written in the English language and conducted on human samples between December 2019 and January 2021 were included.

Results

Hematological changes are not reported in asymptomatic or presymptomatic COVID‐19 patients. In nonsevere cases, hematological changes are subtle, included mainly lymphocytopenia (80.4%). In severe, critically ill patients and those with cytokine storm, neutrophilia, lymphocytopenia, elevated D‐dimer, prolonged PT, and reduced fibrinogen are predictors of disease progression and adverse outcome.

Conclusion

Monitoring hematological changes in patients with COVID‐19 can predict patients needing additional care and stratify the risk for severe course of the disease. More studies are required in Iraq to reflect the hematological changes in COVID‐19 as compared to global data.

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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

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Thu May 06 2021
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Impact of COVID-19 pandemic on healthcare providers: save the frontline fighters
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Abstract<sec><title>Objectives

The objective of this study was to assess the impact of the COVID-19 pandemic on healthcare providers (HCPs) at personal and professional levels.

Methods

This was a cross-sectional descriptive study. It was conducted using an electronic format survey through Qualtrics Survey Software in English. The target participants were HCPs working in any healthcare setting across Iraq. The survey was distributed via two professional Facebook groups between 7 April and 7 May 2020. The survey items were adopted with modifications from three previous studies of Severe Acute Respiratory Syndrome (SARS) and Avia

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The coronavirus-19 (COVID-19) pandemic, triggered by the severe acute respiratory syndrome coronavirus 2, has affected over 100 million people and killed around 2 million individuals. One of the most common chronic illnesses in the world is diabetes, which greatly raises the risk of hospitalization and death for COVID-19 patients.

Objective

This study aims to analyze the novel coronavirus's general characteristics and shed light on COVID-19 and its management in diabetic individuals by measuring some metabolic and inflammatory factors in type 2 diabetic pa

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The potential role of dyslipidemia in COVID-19 severity among Iraqi patients
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The correlation between dyslipidemia and the severity of coronavirus disease 2019 has been widely categorized. Dyslipidemia is one of the most dominant disorders among these patients. Systemic inflammation accompanied by cytokine storm hemostasis modifications and severe vasculitis have all been reported to occur among COVID-19 patients, and these may contribute to some severe complications.

OBJECTIVE:

The aim of this study is to assess the possible relationship between dyslipidemia and the severity of coronavirus disease 2019.

METHODS:

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Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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