Browsing by Author "Okasha, Ahmad"
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Item Analysis of the United Arab Emirates' contribution to the sustainable development goals with a focus on global health and climate change(Emerald Publishing, 2023) Alkhaldi, Mohammed; Moonesar, Immanuel Azaad; Issa, Sahar T.; Ghach, Wissam; Okasha, Ahmad; Albada, Marina; Chelli, Sabrina; Takshe, Aseel A.Purpose: The world is confronted by various current development challenges, including global health security and climate change. The rapid growth of these challenges warned all nations regardless of their development or geographical position. As an emerging international power, the United Arab Emirates (UAE) was among these nations and is viewed as a proactive key actor. Design/methodology/approach: This review was conducted as a thematic synthesis from 27 studies, reports and publications along with authors' insights. Using MS Word and Excel programs, three stages of data exploration, extraction and synthesis and analysis were applied. Data gathering, analysis and thematization and compilation. Findings: The UAE is giving significant attention to global health and climate change. Over the past 20 years, multipolicies, strategies and bodies were developed to lead the national, regional and global SDGs. Global health and climate change became the most two notable priorities on the government agenda and its strategic thinking is that both priorities can no longer be overlooked. Nationally, the UAE has made significant economic, scientific, social and health growth. Building a resilient and world-class healthcare system was one of six national priorities of the achieved UAE National Agenda 2021. Globally, UAE has proved its global health leadership by ensuring lasting and collective multilateral partnerships and collaborations that led to remarkable achievements in global health and climate change. Examples on the global scale: partnership with the World Health Organization (WHO) to target billions of people of the world's population and ensure they get Universal Healthcare Coverage (UHC) without financial hardship, the partnership between UAE and Bill and Melinda Gates Foundation to establish the Global Institute for Disease Elimination (GLIDE) to fight diseases and put an end to polio. Additionally, the state's role in the COVID-19 global efforts such as vaccine development, supply chain and distribution targeted low- and middle-income countries (LMIC). The UAE has shown a constant commitment to climate change mitigation and building a sustainable ecosystem by hosting global organizations, leading initiatives, supporting countries and is now organizing the 28th Conference of the Parties (COP28) this year. Great opportunities can be exploited to promote the country's contributions through further investment in cooperation, research and technology for better knowledge, sound policies, and innovative solutions for all regional and global health and climate change challenges. Originality/value: This review is a fresh evidence-synthesizing attempt to document the role of the UAE. This role is well placed to play an additional major role with all partners to address these pressing challenges by boosting its role, especially in the Middle East region and advancing a new regional-oriented revolutionary expanded developmental plan that centered on low-resource countries empowerment, multilateralism, intersectionality and lasting collaborations. © 2023, Mohammed Alkhaldi, Immanuel Azaad Moonesar, Sahar T. Issa, Wissam Ghach, Ahmad Okasha, Marina Albada, Sabrina Chelli and Aseel A. Takshe.Item Application of PET/CT image under convolutional neural network model in postoperative pneumonia virus infection monitoring of patients with non-small cell lung cancer(Elsevier B.V., 2021-07) Wei, Jing; Zhu, Ronghua; Zhang, Huai; Li, Pingwei; Okasha, Ahmad; Muttar, Ahmed K.H.It was to study the adoption of positron emission computed tomography (PET-CT) based on the convolutional neural networks (CNN) model in the monitoring of postoperative pneumonia virus infection in patients with non-small cell lung cancer (NSCLC). 120 patients with NSCLC were set as the research object. CNN model was constructed and applied to PET-CT images to identify lesions and screen tumor markers for detection. Then, the patients were randomly divided into group A (CT), group B (PET-CT), group C (PET-CT based on artificial neural network model), and group D (PET-CT diagnosis based on CNN model), 30 cases in each group, and infection surveillance was conducted. The result showed that the accuracy (Acc), sensitivity (Sen), and specificity (Spe) of PET-CT image recognition based on the CNN model were 99.31%, 100%, and 98.31%, respectively. The proportion of serum neutrophils, white blood cell count, and PCT content in group D three days after operation were significantly lower than those in groups B, C, and A (P < 0.05). The proportions of patients with surgical wound infection and lung infection in group D were 6.54% and 15.38% respectively, which were significantly lower than those in groups B, C, and A (P < 0.05). The complication rates of patients in groups A, B, C, and D were 32.4%, 30.2%, 28.75, and 8.7%, respectively. The complication rate of patients in group D was significantly lower than that of the other three groups (P < 0.05). In short, PET-CT images based on the CNN model had high accuracy, sensitivity, and specificity in monitoring postoperative pneumonia virus infection in NSCLC patients. Applying it to the patient's virus infection monitoring can effectively prevent the patient's lung and surgical wound infection and improve the patient's postoperative recovery effect. © 2021 The Author(s)Item Data mining in the time of COVID-19(PalArch Foundation, 2020-12-11) Okasha, Ahmad; Kamalov, Firuz; Hamidi, Samer; Roberts, Claire; Abdulnasir, SafaHealthcare organizations, like other organizations, are facing a major global challenge. In a recent Mckinsey survey (From “wartime” to “peacetime”: Five stages for healthcare institutions in the battle against COVID-19, 2020), many consumers indicated that the COVID 19 pandemic has the most significant challenge on their economic and social lives in the last 100 years. Being patient centric rather than reactive is one of the ways to succeed in this uncertain environment. Being patient centric means to identify the needs of patients and design specific programs to address their needs whether they are financial, personal, or clinical. COVID-19 accelerated utilizing data and online applications. Many healthcare organizations have access to consumer related data. Data mining capabilities provide health care organizations with the ability to extract hidden predictive information from large databases. The paper surveyed hospital Chief Information Officers (CIO), health information managers, and healthcare managers to find out measure awareness of data mining applications in healthcare and to determine the use and reason for data mining applications in healthcare. The results indicate that many healthcare organizations are aware of descriptive and simple data mining tools. For more sophisticated data mining tools, most healthcare organization managers in the Middle East as expected are not aware of them. When it comes to using data mining as an application for disease diagnoses, marketing, and education simulation, many healthcare managers indicate that they are already using data mining in these areas. © 2020 Ahmad Okash, Firuz Kamalov, Samer Hamidi, Claire Roberts, Safa AbdulnasirItem Development and Usability Assessment of a Mobile App (Demensia KITA) to Support Dementia Caregivers in Malaysia: A Study Protocol(MDPI, 2022-10) Rashid, Nurul Syaireen A.; Chen, Xin Wee; Mohamad Marzuki, Muhamad Fadhil; Takshe, Aseel A.; Okasha, Ahmad; Maarof, Faridah; Yunus, Raudah MohdThe impact of dementia on caregivers is complex and multi-dimensional. In low- and middle-income settings, caregivers are often left without adequate support, despite their multiple needs. These include health information, caregiving skills, social and emotional support, and access to local resources—all of which can be partially fulfilled by technology. In recent years, mobile apps have emerged and proven useful for caregivers. We found a few existing apps suitable for Malaysian users in terms of affordability and cultural and linguistic compatibility. Our study aims to design a mobile app that suits dementia caregivers in Malaysia and consists of three phases. Phase I is content development that employs Focus Group Discussion (FGD) and Nominal Group Technique (NGT) involving field experts. Phase II comprises a mobile app (Demensia KITA) designed in collaboration with a software developer specializing in mobile health apps. Phase III entails testing the usability of the app using the Malay version of the mHealth App Usability Questionnaire (M-MAUQ). This study protocol elaborates on the rigorous steps of designing a mobile app and testing its usability, along with anticipated challenges. Our protocol will provide insight for future researchers, healthcare providers, and policymakers and pave the way for better use of digital technology in the field of aging and caregiving. © 2022 by the authors.Item Investigating determinants of pro-environmental behaviors amongst UAE university students through Q-methodology(Springer Nature, 2023-12) Takshe, Aseel A.; Hennawi, Maram; Jebril, Sa’eda; Alawi, Shaikha; AlZaidan, Shahad; Okasha, AhmadNumerous high-tech advancements have established a healthy environment, reduced consumer consumption of non-renewable resources, and reduced the total ecological impact on the environment. Despite this technology, many people still do not have sustainable behavior ingrained in them. Environmental sustainability is threatened by human behaviors, and environmental choices made by individuals are correlated with pro-environmental behaviors. This research focuses on the relationship between people and the environment, the difficulties that have arisen as a result, and the factors that influence university students' pro-environmental behaviors. It explores the factors influencing university students in the United Arab Emirates to have positive environmental attitudes and behaviors using the Q methodology. The results elucidate several discourses, including connections between knowledge and attitude, the importance of formal and informal education, and necessary economic policies and incentives. The results of this research are consistent with those of other recent studies that place more emphasis on attitude than motivation when it comes to changing behavior towards the environment. © 2023, Springer Nature Switzerland AG.Item Mathematical model under E-health context for diagnosis of head and neck space Gram infection through CT imaging(Elsevier B.V., 2021-07) Li, Lei; Shi, Shuguang; Miao, Zhongchang; Xu, Jian; Duan, Xinxiu; Okasha, Ahmad; Qeshta, Mohammed HalmiThe study aimed to investigate the head and neck space infection by Gram bacteria using mathematical model-based CT (computer tomography) under e-health (electronic health). Specifically, a total of 180 clinical patients with head and neck space infection were collected as the research subjects. CT/MRI examination was adopted to diagnose the disease. A mathematical model was then established to be applied in CT imaging. The cause and treatment effect were analyzed by summarizing the data, including basic information, bacterial culture, source and extent of infection, serious complications, and other factors. The results showed that the CT/MRI imaging based on the mathematical model can effectively diagnose the disease and assess the disease progress. There were more male patients than female patients with head and neck space infection, and more elderly patients than younger patients. A total of 42 patients had serious complications, accounting for 23.3% of the total patients. The most common one was descending mediastinitis, followed by respiratory obstruction, pneumonia, pericarditis, orbital infection, and multiple organ failure. There were many sources of infection in the head and neck space. The main cause was dental infection, and there were 137 cases, accounting for 76.1% of the total. Among them, odontogenic infections included tooth apical periodontitis, wisdom tooth pericoronitis, and periodontal disease. Other sources of infection included glandular infections, iatrogenic infections, and traumatic foreign bodies. The most common part affected by head and neck space infection was the submandibular space, and other parts included the masseter space, the cheek space, and the sublingual space. Severe complications of head and neck space infection were mainly inferior mediastinitis and respiratory obstruction. In the bacterial culture experiment, a total of 75 bacterial cultures of 180 patients were positive, and 62 strains of bacteria were cultured, including 11 kinds of gram-positive bacteria and 4 kinds of gram-negative bacteria. The main pathogens cultivated were Streptococcus viridans, Staphylococcus aureus, and Klebsiella pneumoniae. In laboratory tests, the values of WBC and hs-CRP in patients with severe complications were significantly higher than those in patients with common head and neck space infection. Imipenem and ornidazole were the most commonly used antibiotics in the clinical treatment of patients with severe complications. In conclusion, head and neck space infection is a serious infectious disease that may be life-threatening and requires timely and effective treatment. © 2021 The Author(s)Item Resource partitioning and hospital specialization(Sage Publications India Pvt. Ltd, 2019) Okasha, AhmadBackground: Organizational scholars have been debating over specialism and generalism, and which environment is better for specialists and for generalists. Methods: This study relies heavily on the work of Okasha (Okasha, 1995, Modeling the determinants of hospital services differentiation and specialization (Dissertation). Virginia Commonwealth University, Richmond) and enhances it with available current literature on the topic. Okasha’s (Modeling the determinants of hospital services differentiation and specialization (Dissertation). Virginia Commonwealth University, Richmond) study tested the use of resource partitioning theory to explain the conversion of generalists to specialists under competitive environments. Results: The anticipated effect of buyers of care on hospital specialization was evident. Recent work on specialization (Eastaugh, 2014, Journal of Healthcare Finance) confirmed the trend. Conclusion: Buyer-related factors and organizational factors were the most important predictors of the positive change in hospital specialization between 1987 and 1993. High competition, the increased pressure from buyers of care, and organizational factors were the most important predictors of the positive change in the hospital specialization measures during that time period. © 2019 Indian Institute of Health Management Research.Item Robotic assisted surgery in the United Arab Emirates: healthcare experts’ perceptions(Springer Nature, 2023-12) Barkati, Nasim; Ntefeh, Noura; Okasha, Ahmad; Takshe, Aseel A.; ElKhatib, Rami; Chelli, SabrinaThe adoption of Robotic Assisted Surgery (RAS) has grown around the world. This is also the case in the Middle East and Gulf region and specifically to the United Arab Emirates (UAE). The perception of RAS has been studied in the USA, Europe, and Canada. However, there is limited research on the perception of RAS in the UAE. The study aims to examine the perception of RAS among healthcare experts in the UAE and potential challenges. This qualitative study is based on interviewing healthcare experts in the UAE. Most of the study participants were clinicians and surgeons. In the UAE, RAS is adopted in general surgery, urology, brain surgery, and obstetrics and gynecology. Our findings show that healthcare experts have positive perceptions of RAS. The cost and lack of RAS training program are considered as challenges to adopting RAS in healthcare practices. More research is encouraged to examine perception variations with surgical practices in the UAE, Gulf and the Middle East. © 2023, The Author(s).Item Ultrasonic diagnosis of functional dyspepsia under adaptive partial differential denoising model and its relationship with Helicobacter pylori infection(Elsevier B.V., 2021-07) Liu, Changming; Tan, Zhi; Yang, Jianqing; Zhang, Chan; Xu, Hongwei; Okasha, Ahmad; Arbab, Ahmed Mohamed HamadThis work was to study the relationship between functional dyspepsia (FD) and Helicobacter pylori (HP) based on the adaptive partial differential denoising model. The adaptive partial differential denoising model was adopted to analyze the ultrasound images, which was then utilized in the ultrasound diagnosis of FD after its related performance was evaluated. Fifty patients with gastrointestinal disease who came to our hospital were recruited and rolled into group A (HP positive) and group B (HP negative), and the clinical symptoms of the two groups were compared. The results showed that the maximum peak signal-to-noise ratio (PSNR) and the running time based on the adaptive partial differential denoising model were both superior to the total variation image restoration (TV) model, with statistical differences (P < 0.05). The PSNR of the partial differential denoising model was superior to that of the TV model, and the mean square error (MSE) was inferior to that of the TV model, both with considerable differences (P < 0.05). For the ultrasound manifestations of the stomach of FD patients, the number of dysfunctional patients in gastric emptying dyskinesias was the largest, accounting for 38%. The overall symptoms of FD patients and HP-infected patients were more severe than those of uninfected patients, especially the symptom of upper abdominal pain, and that in group A was remarkably higher than that of group B (P < 0.05). In summary, the quality of ultrasound images based on the adaptive partial differential denoising model was ideal, and the edge retention capability was strong. In addition, HP was an important factor in causing FD, among which upper abdominal pain was the most obvious. © 2021 The Authors