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Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. These results reflect the overall impact observed following the entire course of the COVID-19 pandemic and are not specific to a particular wave. The analysis revealed that older participants experienced a more pronounced decline in productivity, with a mean decrease of 35% compared to younger participants. Female participants, on average, had a 28% decrease in productivity compared to their male counterparts. Moreover, individuals with lower socioeconomic status exhibited a substantial decline in productivity, experiencing an average decrease of 40% compared to those with higher socioeconomic status. Similarly, participants who slept for fewer hours per night had a significant decline in productivity, with an average decrease of 33% compared to those who had sufficient sleep. The machine learning analysis identified age, specialty, COVID-19 complications, socioeconomic status, and sleeping time as crucial predictors of productivity score. The study highlights the significant impact of post-COVID-19 on the productivity of medical staff and doctors in Iraq. The findings can aid healthcare organizations in devising strategies to mitigate the negative consequences of COVID-19 on medical staff and doctors' productivity.

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

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Publication Date
Sat Sep 12 2020
Journal Name
Al-kindy College Medical Journal
A Brief view on the pediatric COVID- 19 pandemic
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The world is currently challenging the serious effects of the pandemic of the Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). Data on pediatric COVID are rare and scattered in the literature. In this article, we presented the updated knowledge on the pediatric COVID-19 from different aspects. We hope it will increase the awareness of the pediatricians and health care professionals on this pandemic.

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Publication Date
Mon Jun 15 2020
Journal Name
Al-academy
Aesthetics of the Sufi Image and its Representations in Post-Modern Theater Show: فرحان عمران موسى
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  Sufism has aesthetic signs linked to the human spirit and adopts a set of spiritual, motor and tonal practices, let alone the philosophical aspects that have been tackled in the epics, novels and theatrical texts, the theatrical show can recall the Sufi image and its aesthetics within the operating and image system of the theatrical show.. The research problem resides in how to employ the Sufi image in the theatrical show. The research consists introduction of the research subject, the problem, the importance, and objectives represented by uncovering the aesthetic and intellectual representations of the Sufi image in the theatrical show. the theoretical foundation within two sections: the first highlighted the concept of (Sufism a

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of The College Of Languages (jcl)
Die Wirkungen der Nachkriegsliteraur Die Kurzgeschichte " Das Brot" von Wolfgang Borchert als Beispiel Eine analytische Studie The effect of post-war literature / short story ( The Bread )
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Die Zusammenfassung :

In der  Forschung „ Die Wirkungen der  Nachkriegliteratur „ findet man einen Überblick über die Wirkungen der Literatur im Allgemeinen und besonders über die Wirkungen der Nachkriegliteratur in Deutschland. Das Kurzgeschichte „ das Brot“ von Wolfgang Borchert „  wird in dieser Forschung als Beispiel analysiuert, weil sie die Nachteile des Kriegs und ihre Wirkungen auf die Familienbeziehungen behandelt. Die Hauptfiguren der Kurzgeschichte sind ein alter Mann und seine Frau. Der Schriftsteller bestimmt die Rolle der Frauen in Deutschland. Die Frau in dieser Geschichte ist stärker als ihren Mann , denn er war lügner und schwach.

Post-war Literature has an e

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Publication Date
Thu Oct 08 2020
Journal Name
Journal Of Legal Sciences
The Impact of the COVID-19 Pandemic on the Performance of Contractual Obligations
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The global health crisis resulting from the spread of the Corona virus, which the World Health Organization described on January 30, 2020 as a public health emergency of international concern, then returned to describe it as a pandemic on March 11, 2020, and the measures and procedures taken by government authorities in different countries of the world, whether at the highest level of imposing a comprehensive curfew or what is called globally home quarantine and thus disrupting all sectors and activities in the state, whether public or private (with the exception of some sectors such as the health, media and security sectors), or at a lower level than that, such as reducing work rates in different sectors by rates that vary from one country

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Publication Date
Fri Apr 30 2021
Journal Name
Al-kindy College Medical Journal
Assessment of the Awareness of COVID-19 among the Students Enrolled in Different Medical Universities of Pakistan: A Cross Sectional Survey
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Background: The study was designed for the assessment of the knowledge of medical students regarding pandemics. In the current designed study, the level of awareness was checked and the majority of students were found aware of SARS-CoV and SARS-Cov2 (Covid-19).

Objective: To assess the awareness of SARS-CoV and SARS-Cov2 (Covid-19) among medical students of Pakistan.

Subjects and Methods: A cross-sectional survey was carried out in different universities of Pakistan from May to August 2020. A self-constructed questionnaire by Pursuing the clinical and community administration of COVID-19 given by the National Health Commission of the People's Republic of China was used am

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Tue May 10 2016
Journal Name
Iraqi New Medical Journal January
Which medical specialty do I choose? The answer of Iraqi graduated doctors working in Basra
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OBJECTIVE: To determine the preferred specialties of graduated medical doctors working in Basra, and determine the factors behind their preferences. METHODS: The study was conducted in 38 primary health care centres and seven hospitals in Basra from January-June 2014. A cross-sectional study was adopted with the use of a self-administered questionnaire form. Two hundred ninety six graduated doctors were agreed to participate. Chisquare test and logistic regression were used to test the association between deciding a future speciality and influencing factors. RESULTS: The most preferred specialties were radiology and ultrasound, gynaecology and obstetrics, surgery, internal medicine, dermatology and paediatrics. Clinical specialties were sta

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