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.
Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.
Deep Learning Techniques For Skull Stripping of Brain MR Images
The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MoreBusiness organizations strive to reach organizational excellence, in instruction to maintain their position in the market, so the research started from the problem of the weakness of the senior leaders in the two companies investigated in the management and sustainability of work, as well as their inability to face challenges that could affect the work of the two companies in the future, especially the lack of organizational of the future and the prediction of those events, so the two companies seek to explore and invest opportunities to achieve organizational excellence. The research aims to know the role of Ambidexterity leadership behaviors in organizational excellence in my company .and create ideas that will achieve organizati
... Show Moreيتناول هـذا البحث بالتحليل التفاعل و التنسيق بين السياستين الماليـة و النقديـة و اثر هذا التفاعل و التنسيق على الاستقـرار و النمـو الاقتصـادي، و كيف ان الآثار المالية للسياسة النقدية قد تحفز الإجراءات الخاصة بالسياسة النقدية و معالجة الآثـار الجانبيـة و طبيعـة التفاعل و الارتداد بين إجراءات كلتا السياستين و أثرهما في التـوازن الاقتصـادي العــام، و تم في ثنايا البحث توضيح مسوغات التنسيق و مدى ضرورة ذلك بهد
... Show MoreBackground: Kinesiologists, Physical Anthropologists, and Anatomists have all long been captivated by the structure and development of the superficial forearm flexor, the Palmaris longus.
Objective: To study the effect of Palmaris Longus on certain handwriting skills.
Subjects and Methods: Three Palmaris Longus occurrence tests were conducted on 200 students (100 males and 100 females) affiliated to Colleges of Medicine of Baghdad University then the participants were tested for certain handwriting skills to correlate the presence of Palmaris Longus in the dominant side with handwriting.
Results: 89% of all subject
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