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Introduction: Coronavirus disease 2019 (COVID-19) has had a profound impact globally, causing the death of millions of people and deeply affecting socio-psychological, human health, and economic systems, with some nations bearing a disproportionate burden. Despite obesity having been established as one of the major risk factors of COVID-19 severity and other degenerative diseases, the effects that dietary pattern plays in COVID-19 outcomes remain poorly understood. The goal of this study is to look into the connection between eating habits, the number of non-obese and obese people, and COVID-19 outcomes in countries with populations exhibiting normal Body Mass Index (BMI), which is an indicator of obesity. Methods: The analysis includes data from 170 countries. From the 170 countries, we focused on 53 nations where the average, BMI falls within the normal range (18.5 to 24.9). A subset of 20 nations was selected for a more detailed examination, comprising 10 nations with the lowest BMI values within the normal range (18.5-19.8) and 10 nations with the highest BMI values within the normal range (23.5-24.9). We used Artificial Intelligence (AI) and Machine Learning (ML) applications to evaluate key metrics, including dietary patterns (sugar and vegetable intake), obesity prevalence, incidence rate, mortality rate, and Case Fatality Rate (CFR). Results: The results demonstrate a significant correlation between higher obesity prevalence and increased COVID-19 severity, evidenced by elevated incidence, mortality, and CFRs in countries like North Macedonia and Italy. In contrast, nations such as Iceland and New Zealand with well-established healthcare systems revealed low mortality rates and case fatality rates despite variations in dietary habits. The study also revealed that vegetable consumption appears to provide a slight to significant protective effect, suggesting that dietary patterns alone do not consistently predict COVID-19 Outcomes. Conclusion: Data generated from this study showed the crucial role of healthcare infrastructure along with the testing capacity and data reporting in influencing the success of pandemic responses. It also highlights the need to integrate public health strategies, which focus on obesity management and improvement of healthcare preparedness. In addition, AI-driven predictive modeling offers valuable insights that may guide pandemic response efforts in the future, thereby enhancing global health crisis management and mitigating the impact of future health emergencies. 

Artificial intelligence (AI) leverages mathematical algorithms to emulate human cognitive abilities, leading to a transformative impact on the education sector. Educators are at the front lines of implementing AI in the classroom. Recent scientific studies demonstrate the capacity of AI, particularly generative models like ChatGPT, to reshape various aspects of education. In a recent study, we showcased that the integration of both artificial intelligence, specifically ChatGPT, and interactive learning activities significantly enhances the engagement levels of STEM students enrolled in a General Biology course. Furthermore, this combined approach not only boosts student engagement but also demonstrates an improvement in their overall performance within the course. Building on preliminary studies, the objective of this review article is to delineate the diverse applications of generative AI in education. To achieve this objective, we conducted a thorough search across scientific databases, including Google Scholar, Science Direct, government websites, and other resources, to collect relevant papers. Our findings underscore the contributions of generative AI, exemplified by ChatGPT, in enabling students to generate innovative text for written assignments, providing personalized feedback, facilitating adaptive learning, enhancing accessibility to education by eliminating barriers for individuals with disabilities, and supporting research endeavors. 

COVID-19, known as Coronavirus Disease 2019, is a major health issue resulting from novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Its emergence has posed a significant menace to the global medical community and healthcare system across the world. Notably, on December 12, 2020, the Food and Drug Administration (FDA) approved the utilization of the Pfizer and Moderna COVID-19 vaccines. As of July 31, 2022, the United Stated has witnessed over 91.3 million cases of COVID-19 and nearly 1.03 million fatalities. An intriguing observation is the recent reduction in the mortality rate of COVID-19, attributed to an augmented focus on early detection, comprehensive screening, and widespread vaccination. Despite this positive trend in some demographics, it is noteworthy that the overall incidence rates of COVID-19 among African American and Hispanic populations have continued to escalate, even as mortality rates have decreased. Therefore, the objective of this research study is to present an overview of COVID-19, spotlighting the disparities among different racial and ethnic groups. It also delves into the management of COVID-19 within the minority populations. To reach our research objective, we used a publicly available COVID-19 dataset from kaggle: https://www.kaggle.com/datasets/paultimothymooney/covid19-casesand- deaths-by-race. In addition, we obtained COVID-19 datasets from 10 different states with the highest proportion of African American populations. Many considerable strikes have been made in COVID-19. However, success rate of treatment in the African American population remains relatively limited when compared to other ethnic groups. Hence, there arises a pressing need for novel strategies and innovative approaches to not only encourage prevention measures against COVID-19, but also to increase survival rates, diminish mortality rates, and ultimately improve the health outcomes of ethnic and racial minorities.