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.
The experiment was conducted using Potato( Solanum tuberosum L.) at the eastern Radwaniyah at private field during fall season 2020/2021 and spring 2021 to study the effect of nitrogen levels to 350, 275, 200 kg N h-1 ( N1, N2, N3) and phosphorous to 100, 180, 360 kg P2O5 h-1 ( P1, P2, P3) and potassium to 100, 200, 300 kg K2O h-1 ( K1, K2, K3) to vegetative growth and yield of industrial potato, The seeds of the hybrid potato Sinora, Class A, were planted in the fall season on 15/9/2020 and Elite in the spring season on 31/1/2021. The experimental fertilizers were added in four batches and in proportions according to the stages of plant age, Factorial experiment with RCBD using three replications. The results showed that changing t
... Show MoreThere were many ideas and opinions on the linkage between growth and economic reform in both developed and developing countries. The relationship is, of course, existed. Therefore, this research comes to analyses it in the Iraqi economy. This study is based on a hypothesis that the economic reformation in Iraq leads to lag level of growth with the of high rates of inflation. However, the study is designed to be included five sections. It found a positive relationship between the economic reformation and slowing of economic growth, in which the specified hypothesis is not fit to the economic reality in Iraq after 2003 &
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Objectives: To assess patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention, and to find out the relationship between patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention
Methodology: A descriptive design was carried out at Al- Nasiriyah Heart Center in Thi-Qar Governorate for the period between May 19th, 2022 to October 25th, 2022. A non-probability sampling was used among (50) patients after their Percutaneous Coronary Intervention. The study instrument that used to collect data was composed of three parts namely: sociodemographic charac
... Show MoreThe current study aimed to reveal the moral values available in the Arabic language textbook (Al-Mu’nes) for grades eleven and twelve for post-basic education in the Sultanate of Oman. The researcher adopted the descriptive approach using the sentence as measuring unit in the analysis process. The five fields of moral values and their subcategories values represented the categories of the analysis. Iterations of values and the percentages of iteration were calculated in those textbooks. Moreover and the analysis and stability of the process were confirmed.
After referring to previous studies, it was possible to de
... Show MoreSpray pyrolysis technique (SPT) is employed to synthesize cadmium oxide nanostructure with 3% and 5% Cobalt concentrations. Films are deposited on a glass substrate at 350 ᵒC with 150 nm thickness. The XRD analysis revealed a polycrystalline nature with cubic structure and (111) preferred orientation. Structural parameters represent lattice spacing, crystallite size, lattice parameter and dislocation density. Homogeneous surfaces and regular distribution of atoms were showed by atomic force microscope (AFM) with 1.03 nm average roughness and 1.22 nm root mean square roughness. Optical properties illustrated a high transmittance more than 85% in the range of visible spectrum and decreased with Co concentration increasing. The absorption
... Show MoreThe research aims to measure the impact of envy on job stress because the topic of envy represents a negative emotion that exists at all organizational levels, which may cause stress in the work environment.
The Research problem is represented by the lack of perception of most of the faculty staff on the negative effects of envy on their well-being in the Technical College of Management - Baghdad, and what is the impact level of envy on their job stress.
To achieve this, the scale of envy was based on two dimensions (being envied, Envying others), While the job stress scale was based on seven dimensions (workload, conflict role, Family factors, work environment, work relationships
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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