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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
Thu Oct 12 2023
Journal Name
Mustansiriyah Journal Of Pure And Applied Sciences
Cavitation microbubbles in the medical ultrasound imaging: A Review
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Ultrasound is a mechanical energy which can generate altering zones of compression and rarefaction along its path in the tissues. Ultrasound imaging can provide a real time screening for blood and multiple organs to aiding the diagnostic and treatment. However, ultrasound has the potential to deposit energy in the blood and tissues causing bio effects which is depending on ultrasound characteristics that including frequency and the amount of intensity. These bio effects include either a stable cavitation presented non thermal effects or inertial cavitation of harmful effect on the tissues. The non-thermal cavitation can add features in diagnostic imaging and treatment more than the inertial cavitation. Ultrasound Contrast agents are a micro

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Publication Date
Fri Apr 30 2021
Journal Name
Al-kindy College Medical Journal
Al-Kindy College Medical Journal: Time to Move Forward
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It is well- known that the distinguished scholastic journal is a crucial cornerstone, which contributes to the scientific integrity of a particular academic institution. The establishment of the Al-Kindy College of Medicine (AKCM), University of Baghdad, in 1998 urged the need to issue Al-Kindy College Medical Journal (KCMJ).

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Manegment of the medical waste in the kindy hospital
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The problem of medical waste over the past tow decades has emerged as one of the most important issues.

Which have negative effects on health and the environment ,and as a result specialists looked into the field.

Public health and research issues . This phenomenon in all its dimensions and efforts made For their containment through the development of health and environmental controls for the disposal of such wastes.

In a safe manner starting form the source of these wastes and the various health organizations are  finished The final treatment ,and this is why the producers of hazardous medical waste.        &nb

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Publication Date
Tue Dec 20 2022
Journal Name
2022 International Conference On Computer And Applications (icca)
Smart Healthcare Medical Bracelet using the Internet of Things
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Publication Date
Tue Dec 20 2022
Journal Name
2022 International Conference On Computer And Applications (icca)
Smart Healthcare Medical Bracelet using the Internet of Things
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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
The Effects of Long-Term Operation and High Temperature on Material Properties of Austenitic Stainless Steel Type 321H
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Changes in mechanical properties of material as a result of service in different conditions can be provided by mechanical testing to assist the estimation of current internal situation of these materials, or the degree of deterioration may exist in furnaces serviced at high temperature and exceed their design life. Because of the rarity works on austenitic stainless steel material type AISI 321H, in this work, ultimate tensile strength, yield strength, elongation, hardness, and absorbed energy by impact are evaluated based on experimental data obtained from mechanical testing. Samples of tubes are extracted from furnace belong to hydrotreaterunit, also samples from un-used tube material are used to make comparisons between these properti

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Publication Date
Thu Aug 22 2024
Journal Name
وقائع المؤتمر العلمي الدولي التاسع للعلوم الانسانية والتربوية
تأثير بعض العقائد الدينية على الشخصية اليهودية
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Publication Date
Thu Nov 14 2024
Journal Name
مجلة مركز بابل للدراسات الانسانية
تأثير المقامة العربية على المقامة العبرية الاندلسية
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Finding the best estimation of generalized for failure rates by using Simulation
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The statistical distributions study aimed to obtain on best descriptions  of variable sets phenomena, which each of them got one behavior of that distributions .  The estimation operations study for that distributions considered of important things which could n't canceled in variable behavior study, as result  this research came as trial for reaching to best method for information distribution estimation which is generalized linear failure rate distribution, throughout studying the theoretical sides by depending on statistical posteriori methods  like greatest ability, minimum squares method and Mixing method (suggested method).        

The research

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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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