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.
Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po
Witnessing human societies with the turn of the century atheist twenty huge revolution in information , the result of scientific and technological developments rapidly in space science and communications , and that made the whole world is like a small village not linked by road as it was in ancient times, through the rapid transportation as was the case a few years ago , thanks to the remote sensing devices that roam in space observant everything on the ground , that the information networks that overflowed the world a tremendous amount of information provided for each inhabitants of the earth , which made this information requirement for human life and human survival and well-being , as it has allowed that information to humans opportun
... Show MoreDiabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
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The aim of the research is to demonstrate the impact of long-term investment on profitability, and in order to achieve this goal, long-term investment was chosen, represented by (the ratio of long-term investments to total investments, the ratio of long-term investment to the total (deposits) as independent variables, and studying its impact on the dependent variable, which is profitability as measured by the rate of return on investments, the rate of return on equity. In order to reach the results, the inductive approach and the analytical descriptive approach were used, and the research found a significant impac
... Show MoreThe investment climate is the main engine of economic development. If an appropriate and attractive investment climate is created that takes into account economic, administrative, political and environmental issues, it will contribute to the development of industry, transfer of technology, diversification of agricultural production, increased productivity, the promotion of a green economy and support for sustainable and inclusive growth. Thus, analyzing the investment climate of a country can provide reasons and roots for the complexity of the problems in the economy. In the Iraqi economy, the problem has not been rooted in the economy, but the roots of the problem are deeper and inherent in the management of the economy. Investm
... Show MoreThe research aims to identify the extent to which Iraqi private banks practice profit management motivated by reducing the taxable base by increasing the provision for loan losses by relying on the LLP it model, which consists of a main independent variable (net profit before tax) and independent sub-variables (bank size, total debts to total equity, loans granted to total obligations) under the name of the variables governing the banking business. (Colmgrove-Smirnov) was used to test the normal distribution of data for all banks during the period 2017-2020, and then find the correlation between the main independent variable sub and the dependent variable by means of the correlation coefficient person, and then using the multiple
... Show MoreThis study was carried out in order to determine the toxic, mutagenic and antimutagenic effects for Mallow (Malva parviflora) in comparison to its mutagenic effect of Ultraviolet (UV) because it is consider physical mutagen by using parameters for the extract pri , with , post UV exposure by using bacterial system (G-system). The used system consisted of three isolates G3 Bacillus spp., G12 Arthrobacter spp. and G27 Brevibacterium spp.. The study depended on recording survival fraction (Sx) for studying the effects and induction of Streptomycin and Refampicin resistance mutants as a genetic markers.Water Extract was prepared from fresh and dry mallow leaves, stems, flowers and roots, in optimum concentration equal to (125µg/ml) which is
... Show MoreSurrealism is a twentieth-century literary and artistic movement oriented toward the liberation of the mind. Surrealism is a reaction to the philosophy of rationalism which was believed to be the cause of the disaster of World War I. It emphasizes the expression of the imagination as revealed in dreams and presented without conscious control, the unexpected juxtapositions of objects, the withdrawal of the self, and the exploitation of chance effects.
Surrealism began in Paris in the early 1920s, as Europe emerged from the devastation of World War I. A group of writers, artists, and filmmakers, led by the poet André Breton, adopted the word surréaliste (meaning, roughly, "super-real") as a label for their artistic activities. Influen