Application of Artificial Intelligence in Pediatric Pulmonology: Current Scenario and Future Prospective

Background: Artificial intelligence is well poised to be a multi-dimensional resource for children and their health in the future. Recent advancement in machine learning and algorithms have helped tackle diseases like asthma, pneumonia, and lung nodules. Objectives: Present study aims to provide a detailed overview of AI application in Pediatric Pulmonology. Methods: Many articles, published in review journals have been included to write the current review. The literature search was done by using electronic databases such as PubMed, Google Scholar, ResearchGate, Frontiers. Pictorial descriptions of AI efficiency have been included for better understanding. Studies have been reviewed to highlight the pandemic scenario and its effect on children. Results: Various studies have shown promising results of AI application in Pediatric Pulmonology through efficient imaging and digital technology-based devices. The utility of AI technique has been included under the following subheadings 1) Artificial Intelligence in Pediatric Auscultation, 2) Artificial Intelligence in Pediatric Imaging, 3) Artificial Intelligence based Pediatric PFTs, 4) Machine learning in prediction of childhood asthma persistence, 5) AI in Pneumonia diagnosis in children, 6) AI in Pediatric Pulmo-oncology, 6) Covid-19 scenario, 7) Current and Future Perspective of AI, 8) Challenges and Pitfalls of AI in Pediatric Pulmonology. Conclusion: AI technology has come a long way in the field of Pediatrics especially during the post-covid scenario through novel digital devices and automation. Lack of technology awareness, funding and AI in study curriculum are a few challenges faced by the health care professionals currently. These limitations must be addressed for more clinical utility in daily practice

Racial/ethnic disparities in annual mammogram compliance among households in Little Haiti, Miami-Dade County, Florida

Abstract Introduction Breast cancer is the most commonly diagnosed cancer and the 2nd leading cause of cancer-related deaths among women in the U.S. Although routine screening via mammogram has been shown to increase survival through early detection and treatment of breast cancer, only 3 out of 5 women age ?40 are compliant with annual mammogram within the U.S. and the state of Florida. A breadth of literature exists on racial/ethnic disparities in compliance with mammogram; however, few such studies include data on individual Black subgroups, such as Haitians. This study assessed the association between race/ethnicity and annual mammogram compliance among randomly selected households residing in the largely Haitian community of Little Haiti, Miami-Dade County (MDC), Florida. Methods This study used cross-sectional, health data from a random-sample, population-based survey conducted within households residing in Little Haiti between November 2011 and December 2012 (n = 951). Mammogram compliance was defined as completion of mammogram by all female household members within the 12 months prior to the survey. The association between mammogram compliance and race/ethnicity was assessed using binary logistic regression models. Potential confounders were identified as factors that were conservatively associated with both compliance and race/ethnicity (P???0.20). Analyses were restricted to households containing at least 1 female member age ?40 (n = 697). Results Overall compliance with annual mammogram was 62%. Race/ethnicity was significantly associated with mammogram compliance (P = 0.030). Compliance was highest among non-Hispanic Black (NHB) households (75%), followed by Hispanic (62%), Haitian (59%), and non-Hispanic White (NHW) households (51%). After controlling for educational level, marital status, employment status, the presence of young children within the household, health insurance status, and regular doctor visits, a borderline significant disparity in mammogram compliance was observed between Haitian and NHB households (adjusted odds ratio = 1.63, P = 0.11). No other racial/ethnic disparities were observed. Discussion Compliance with annual mammogram was low among the surveyed households in Little Haiti. Haitian households underutilized screening by means of annual mammogram compared with NHB households, although this disparity was not significant. Compliance rates could be enhanced by conducting individualized, mammogram screening-based studies to identify the reasons behind low rate of compliance among households in this underserved, minority population

Artificial intelligence in sickle disease

Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, and treatment options for many pathologies, including sickle cell disease (SCD). AI has started new ways to improve risk stratification and diagnosing SCD complications early, allowing rapid intervention and reallocation of resources to high-risk patients. We reviewed the literature for established and new AI applications that may enhance management of SCD through advancements in diagnosing SCD and its complications, risk stratification, and the effect of AI in establishing an individualized approach in managing SCD patients in the future. Aim: to review the benefits and drawbacks of resources utilizing AI in clinical practice for improving the management for SCD cases.Open Access funding provided by the Qatar National Library.Scopu

Using practical inquiry to improve third-grade secondary students' learning (Action research)

هدف البحث إلى استكشاف الكيفية التي يسهم بها استخدام الاستقصاء العملي في تحسين تعلم طالبات الصف الثالث الثانوي في مادة الحديث والثقافة الإسلامية. ولتحقيق هذ الهدف؛ اتبعت الباحثة منهج البحث الإجرائي الذي يمكّن الممارسين من تفحص ممارساتهم وتحسينها، واستخدمت أداتين نوعيتين هما: الملاحظة والأسئلة المفتوحة، وحللت البيانات بأسلوب الترميز المفتوح. وأظهرت النتائج أن استخدام الاستقصاء العملي أسهم في تحسين تعلم الطالبات من خلال أربعة جوانب رئيسة: تعزيز التعلم التعاوني، وتنمية مهارات التفكير، وتنمية مهارات حل المشكلات، وربط محتوى الدرس بالحياة الواقعية. وأسهم هذا البحث الإجرائي في تعزيز الأداء التدريسي للمعلمة الباحثة من خلال تطوير إجراءات الاستقصاء العملي لتتناسب مع طالبات الصف الثالث الثانوي ومحتوى المادة الدراسية، وزيادة قناعتها بإمكانية تطبيقه في المرحلة الثانوية. وفي ضوء النتائج؛ قدم البحث توصيات لدعم استخدام الاستقصاء العملي في المرحلة الثانوية، منها: تنظيم الجدول المدرسي بمرونة ليسمح بوقت كافٍ لتطبيق الاستقصاء، وتوفير الإنترنت، وتفعيل التعلم المدمج في المدارس الثانوية.The purpose of the study was to explore how practical inquiry enhances third-grade secondary students' learning in Hadith and Islamic culture. The researcher followed an action research approach that enables practitioners to examine and improve their practices. Two qualitative instruments were used to collect data: Observation and open-ended questions. The data were analyzed by open coding. Results showed that the use of practical inquiry improved student learning through four main aspects: promoting cooperative learning, developing thinking skills, developing problem-solving skills, and linking the lesson content to real life. This action research helped improve the researcher's teaching performance by developing the practical inquiry procedures to be appropriate for third-grade secondary students and the subject, and strengthened her belief that practical inquiry could be used in secondary education. The research made recommendations to support practical inquiry in secondary schools, including flexible organization of the school schedule to allow sufficient time to conduct inquiry, provision of Internet, and activation of blended learning in secondary schools

Application Maintenance Offshoring Using HCI Based Framework and Simple Multi Attribute Rating Technique (SMART)

Over the last two decades, the rapid expansion of the Internet has prompted a growing number of enterprises to deploy their work globally. Companies are increasingly reliant on software systems, which need ongoing modification, maintenance, and upgrades. The maintenance phase consumes approximately 80% of the total software budget. Hence, companies have been eagerly looking for offshore outsourcing of these software systems. Choosing the best sourcing model for software maintenance projects remains elusive and challenging due to a variety of technological, social, and political factors. This study aims to analyze application maintenance offshoring related factors and addresses its decision-making process. To achieve the study objectives, factors of two datasets are analyzed based on standard deviation, mean and mean error. The Critical Success Factors (CSFs) are examined thoroughly to explore their impact on decision-making process. Additionally, the study proposes a sourcing framework based on CSFs that uses the Human Computer Interaction (HCI) principles. This framework assists clients and vendors to evaluate the projects prior to offshoring decisions. To enhance decision-making process, a case study is conducted in the Information Technology (IT) industry and the Simple Multi Attribute Rating Technique (SMART) is applied. As the results show, SMART ranks the available options and helps in making effective offshoring decisions

OffshoringDSS: An Automated Tool of Application Maintenance Offshoring

The rapid spread of the internet over the last two decades has prompted more and more companies to deploy their work internationally. The offshoring strategy enables organizations to cut down costs, boost shareholder value, acquire a competitive advantage, reduce cycle time, increase workforce flexibility, generate revenue and focus on their core business. The number of worldwide software development projects has increased due to globalization. Global Software Development (GSD) projects are forecast to grow by 20% to 30% in countries like India and China. The outsourcing experts choose one of the suitable models from the available global delivery options to deliver services in the global software paradigm. However, adopting the appropriate model for application maintenance is a complicated process. In addition, the right model is selected based on various influencing factors, type of the project and client requirements. Additionally, sufficient domain expertise is necessary for the decision making of offshore outsourcing. Currently, there is no dynamic and automated tool for the decision making of application maintenance offshoring. Therefore, this study presents an Offshoring Decision Support System (OffshoringDSS), an automated and novel tool to make the offshoring decisions of application maintenance. The suggested tool is based on the Analytic Hierarchy Process (AHP) technique. The tool automatically performs all the calculations involved in the decision making and ranks the sourcing models

OffshoringDSS: An Automated Tool of Application Maintenance Offshoring

The rapid spread of the internet over the last two decades has prompted more and more companies to deploy their work internationally. The offshoring strategy enables organizations to cut down costs, boost shareholder value, acquire a competitive advantage, reduce cycle time, increase workforce flexibility, generate revenue and focus on their core business. The number of worldwide software development projects has increased due to globalization. Global Software Development (GSD) projects are forecast to grow by 20% to 30% in countries like India and China. The outsourcing experts choose one of the suitable models from the available global delivery options to deliver services in the global software paradigm. However, adopting the appropriate model for application maintenance is a complicated process. In addition, the right model is selected based on various influencing factors, type of the project and client requirements. Additionally, sufficient domain expertise is necessary for the decision making of offshore outsourcing. Currently, there is no dynamic and automated tool for the decision making of application maintenance offshoring. Therefore, this study presents an Offshoring Decision Support System (OffshoringDSS), an automated and novel tool to make the offshoring decisions of application maintenance. The suggested tool is based on the Analytic Hierarchy Process (AHP) technique. The tool automatically performs all the calculations involved in the decision making and ranks the sourcing models

Effect of the molar ratio of (Ni2+ and Fe3+) on the magnetic, optical and antibacterial properties of ternary metal oxide CdO–NiO–Fe2O3 nanocomposites

Abstract In this work, the effect of the molar ratio of (Ni2+ and Fe3+) on the properties of CdO–NiO–Fe2O3 nanocomposites was investigated. The synthesis of CdO–NiO–Fe2O3 nanocomposites was carried out by self-combustion. XRD, UV–Vis, PL and VSM were used to describe the physical properties of the materials. The results showed significant progress in structural and optical properties supporting antibacterial activity. For all samples, the particle size decreased from 28.96 to 24.95 nm with increasing Ni2+ content and decreasing Fe3+ content, as shown by the XRD pattern, which also shows the crystal structure of cubic CdO, cubic NiO, and cubic γ-Fe2O3 spinel. The Ni2+ and Fe3+ contents in the CdO–NiO–Fe2O3 nanocomposites have also been shown to enhance the ferromagnetic properties. Due to the significant coupling between Fe2O3 and NiO, the coercivity Hc values of the samples increase from 66.4 to 266 Oe. The potential of the nanocomposites for antibacterial activity was investigated against Gram-positive (Staphylococcus aureus) and Gram-negative (Pseudomonas aeruginosa, Escherichia coli, and Moraxella catarrhalis) bacteria. Comparison of P. aeruginosa with E. coli, S. aureus and M. catarrhalis showed that it has a stronger antibacterial activity with a ZOI of 25 mm

ON-1 and BA-IX Are the Dominant Sub-Genotypes of Human Orthopneumovirus A&B in Riyadh, Saudi Arabia

Human orthopneumovirus (HOPV) is the major viral pathogen responsible for lower respiratory tract infections (LRTIs) in infants and young children in Riyadh, Saudi Arabia. Yet, predominant HOPV subtypes circulating in this region and their molecular and epidemiological characteristics are not fully ascertained. A total of 300 clinical samples involving nasopharyngeal aspirates (NPAs), throat swabs, and sputum were collected during winter seasons of 2019/2020 and 2021/2022 for HOPV subtyping and genotyping. Of the 300 samples, HOPV was identified in 55 samples (18.3%) with a distinct predominance of type A viruses (81.8%) compared to type B viruses (18.2%). Importantly, the ON1 strain of HOPV-A and BA-IX strain of HOPV-B groups were found to be responsible for all the infections. Sequence analysis revealed a duplication region within 2nd HVR of G protein gene of ON1 and BA-IX strains. This nucleotide duplication exerted a profound effect on protein length and affinity towards cell receptors. Further, these modifications may aid the HOPV in immune evasion and recurrent infections. Data from this study showed that ON-1 genotype of HOPV-A and BA-IX genotype of HOPV-B were dominant in Riyadh, Saudi Arabia. Further, a duplication of sequence within 2nd HVR of G protein gene was found