Abstract The importance of artificial intelligence these days is growing significantly in the field of biomedical applications.The methods of AI technology can play a vital role in providing solutions for the diagnosis of mental health disorders. After the Covid-19 outbreak, Depression, a physiological and psychological disorder, significantly impacts the quality of life and daily functioning of individuals. Among the various types of depression, Major depressive disorder (MDD) is a well-known health issue found in almost one in ten individuals. The AI technology can definitely help with the prediction and diagnosis of depression using various machine learning classifiers. The AI concept can fill the gap between the traditional method of diagnosis with the machine learning approaches. The aim of our work is to implement the machine learning techniques for the detection of depression. With this view in mind, we are using XGBoost & CatBoost advanced tree structured models for monitoring of MDD patients. The traditional machine learning classifiers are applied to the EEG signals for depression prediction. The experiment is carried out with the help of seven time-frequency domain & non-linear features for accurate diagnosis. The use of EEG signals with machine learning algorithms is utilized for classifying MDD and healthy controls. The highest accuracy achieved is 98.00% with the XGBoost algorithm. The suggested method showed promise as a helpful computational tool for psychiatric research by successfully differentiating depressed patients from healthy controls. This work adds to the expanding body of literature by comparing ensemble-based classifiers using EEG data and highlighting their advantages and disadvantages, rather than acting as a ready-to-use diagnostic system. Before being used in real-world situations, additional clinical validation is required, even though the approaches obtain excellent accuracy on research data.

The importance of artificial intelligence is growing. The adoption of it in public administration has the potential to enhance transparency, efficiency, and responsiveness, ultimately creating greater public value (Babšek et al. 2025). Using artificial intelligence technologies in government improves policy-making processes, public service delivery, and the internal management of public administrations (van Noordt and Misuraca 2022). This study aims to analyse constraining factors that influence the strategic decision-making support within public administration based on artificial intelligence.

Artificial intelligence (AI) can completely transform drug development methods by delivering faster, more accurate, efficient results. However, the effective use of AI requires the accessibility of data of excellent quality, the resolution of ethical dilemmas, and an awareness of the drawbacks of AI-based techniques. Moreover, the application of AI in drug discovery is gaining popularity as an alternative to both the complex and time-consuming process of discovering as well as developing novel medications. Importantly, machine learning (ML) as well as natural language processing, for example, may boost both productivity as well as accuracy by analyzing vast volumes of data. This review article discusses in detail the promise of AI in drug discovery as well as offers insights into various topics such as societal issues related to the application of AI in medicine (e.g., legislation, interpretability and explainability, privacy and anonymity, and ethics and fairness), the importance of AI in the development of drug delivery systems, causability and explainability of AI in medicine, and opportunities and challenges for AI in clinical adoption, threat or opportunity of AI in medical imaging, the missing pieces of AI in medicine, approval of AI and ML-based medical devices.

State institutions that provide public services needed by citizens are called 'public administration'. The understanding of public administration has changed over time. This process of change consists of the 'classical public administration approach', the essence of which is centralized bureaucracy, and the 'new public administration approach', the essence of which is that the management approach applied in the private sector can also be applied in public administration. Recently, new management approaches in public administration in developed countries have also attracted attention. The digital age approach is seen as a prominent approach in this sense. It is a known fact that public services provided to citizens are significantly affected by the digital age approach. In this sense, the use of artificial intelligence in terms of increasing quality, effectiveness and productivity while providing public services to citizens comes to the forefront. The focus of the study is to conduct a analysis of the effects of artificial intelligence on public administration. First of all, an extensive literature review was conducted based on books, research theses, articles and expert opinions in the relevant discipline. In this context, the importance of artificial intelligence, which is an important phenomenon of the digital age, in terms of today's public administration understanding, in which areas of public administration it can be effective, the results it will have in public services and examples of artificial intelligence applications in public administration are discussed. As a result of the study, although it is thought that artificial intelligence may create problems in terms of security in the long term, it is also seen that it can provide advantages especially in terms of service quality, productivity and effectiveness increase due to the continuous change in technology in the world. In addition, considering that the developments in the field of artificial intelligence continue rapidly, the necessity of utilizing artificial intelligence in public administrations of all countries following the technology is also seen as a result of the study. The study is expected to contribute to the effective implementation of artificial intelligence applications in the field of public administration by increasing the level of knowledge of the relevant segment

Artificial Intelligence (AI) tools are rapidly transforming the landscape of modern science, engineering, and technological research and innovation. Their ability to process vast datasets, identify complex patterns, and generate predictive models far surpasses human capabilities, leading to accelerated discovery and unprecedented advancements across diverse fields. In scientific research, AI algorithms are instrumental in analyzing genomic data, predicting protein structures, and simulating complex environmental systems, significantly shortening the time required for breakthroughs in areas like medicine, climate science, and materials science. In engineering, AI is revolutionizing design optimization, predictive maintenance, and autonomous systems. Engineers are leveraging AI-powered design tools to create more efficient and sustainable structures, while predictive maintenance algorithms are reducing downtime and improving the reliability of critical infrastructure. The development of self-driving cars, autonomous robots, and smart manufacturing processes is heavily reliant on the sophisticated AI algorithms that enable these systems to perceive, learn, and adapt to their environments. Furthermore, AI is driving innovation in technological research by enabling the development of novel algorithms, hardware architectures, and computing paradigms. AI is being used to design more energy-efficient processors, create advanced materials with tailored properties, and develop new methods for data storage and retrieval. The ability of AI to automate repetitive tasks, generate hypotheses, and identify unexpected correlations is freeing up researchers to focus on more creative and strategic aspects of their work. By augmenting human intelligence and accelerating the pace of experimentation, AI tools are proving indispensable for pushing the boundaries of scientific knowledge, engineering prowess, and technological advancements, ultimately shaping a future driven by intelligent systems and data-driven insights.

In the current era, the role of artificial intelligence is considered important in many aspects not only for environmental sustainability but also for sustainable development in general. Considering the importance of artificial intelligence, this study aims to investigate the impact of artificial intelligence on carbon emissions for a group of twenty-one panel countries by using data from 2010 to 2020. The study employed second-generation panel data econometric tests with nonparametric panel data tests for estimations. The results highlighted that the role of artificial intelligence is crucial for achieving a sustainable environment, as its coefficient is negative for all three models. Specifically, AI has a negative and significant influence on CO2 emissions in Model 1 but a nonsignificant influence in Model 2 across quantiles. A 1% change in the AIPTNTS will cause a decrease in CO2 emissions of -0.009 in Q25, -0.047% in the median quantile, -0.13% in Q75 and − 0.18% in Q90, with a high significance of 1% in Model. This finding suggests that AI largely reduces CO2 emissions in high-carbon-emitting economies. Moreover, income causes carbon emissions to increase; however, the nonlinear term of income curbs carbon emissions, confirming the environmental Kuznets curve (EKC) hypothesis. The effects of human capital, clean energy and renewable energy on carbon emissions are negative, i.e., they help to decrease carbon emissions. The interactive or joint effect of artificial intelligence and clean energy electricity output also helps to decrease carbon emissions in selected countries. In terms of policy recommendations, the study encourages investment in artificial intelligence, increasing the share of clean energy and renewable energy electricity in total energy shares and investment in human capital to achieve a sustainable environment.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-20613-6.

Information technologies are advancing at an ever-accelerating pace, causing changes in the ‎accounting profession. Therefore, universities are forced to periodically assess the demands of ‎organizations on public accountants. The results of the business field now require academia to ‎strengthen the learning of information technology (ICT) in the public accounting program ‎classroom. The research analyzes the academic curricula of several universities, the importance ‎of updating the curricula of the public accounting degree is analyzed, where the importance ‎of incorporating the subject of digital innovation is reflected, such as the proposal of the ‎Syllabus with the topics that should be addressed, with sufficient credit hours, where the ‎automation of processes, systematic language, artificial intelligence and the analysis of Big ‎Data are taught, the focus is directed on the current analysis of academic curricula and the ‎analysis of the work of accountants is being transformed into the digital age in organizations, ‎so that they are competent in the new digital age‎.

The main reason why a modern business needs Enterprise Resource Planning (ERP) systems is that the latter offers an all-in-one solution to some of the most fundamental operations a business has, like finance, supply chain, human resources, customer relationship management and others. But ERP implementations are full of risks in terms of security, operational efficiency, compliance as well as financial sustainability. Other regulations like the General Data Protection Regulation (GDPR) the Sarbanes-Oxley Act (SOX) and any compliance standards in the industry place an extra burden on the entities that implement an ERP system. Elements of risk considered in this paper in terms of ERP implementations include organizational resistance, data security vulnerabilities, financial limitations, and third-party risks. It also recalls compliance frameworks that regulate the governance of ERP and explores the best practices in overcoming regulatory risks. It also considers how the emerging technologies can be used in enhancing the risk management and compliance in ERP and the importance of artificial intelligence (AI), blockchain, robotic process automation (RPA), and advanced analytics. The technologies are advanced to increase predictive risk detection, automated compliance, and secure data in ERP systems. The future trends seem to demonstrate greater regulatory attention, the rise of cloud EVP options, and the inclusion of IoT to view the risks in real-time. To conclude this paper, the author has offered several major recommendations to be used by the organizations to improve their risk management strategies concerning ERP, such as centralized governance compliance, automation using artificial intelligence and data security, and blockchain-based compliance auditing. By promoting prior research and highlighting the most serious cases of knowledge gaps in the field, the current paper adds to the existing body of information on the topic of ERP governance and risk mitigation. Research results can be of great help to scholars, information technology practitioners, and entrepreneurs interested in a secure and compliant ERP implementation in a growing regulatory environment.

The emergence of an explosive number of digital learning environments has made Artificial intelligence (AI) a disruptive force in online education in particular. Educational systems that include AI tools (such as data analytics, machine learning and natural language processing) are increasingly being used with an aim to serve multiple learners needs, enhance the effectiveness of the teaching approach, and augment the learning experience. AI has disrupted the online learning experience by providing greater efficiency and effectiveness in teaching and learning through intelligent feedback mechanisms, personalization and automation. This paper examines the situation on the ground over awareness and the use of AI tools by online educators and learners. The application of AI in some critical sectors like virtual assistants, automated essay evaluation, personalized learning systems, and intelligent tutoring systems has redefined the traditional practice of learning. The paper highlights the degree and manner of AI implementation in online learning settings through a comprehensive exploration of a number of AI-based products, which include virtual companions, smart learning platforms, and AI tutors. The study classifies usage by length of time, types of tools used, and whether it was used frequently and how well it was perceived by using data provided by academic institutions, along with feedback of learners. The results show that AI is becoming more important for individualized instruction, automated evaluation, and immediate feedback, all of which greatly improve student engagement and achievement. The importance of AI in improving results in online education has been highlighted by this study.

The importance of artificial intelligence (AI) in enhancing Mobile Communication (MC) is covered in this abstract, especially in light of the developing 5G and impending 6G networks. The study examines a number of AI methods, including fuzzy logic, reinforcement learning and neural networks, how they are used in MC. It draws attention to how AI might improve the efficiency of networks, solve problems, and meet the rising demand for mobile services that are quicker, more dependable, and more customized. While taking into account the ethical and technological requirements for AI integration, the paper also looks at how AI can affect future technologies, such as intelligent traffic management, maintenance prediction, and tracking the environment. In order to secure responsible AI development, the article highlights the necessity of cooperation between industry, academia, and government. In the end, it offers a thorough analysis of how AI can transform mobile communication, shedding light on the potential advantages and difficulties of implementing AI in networks of the future.

This study aims to explore the role and degree of artificial intelligence (AI) usage in enhancing the learning of volleyball among students in colleges of physical education. Specifically, it investigates students’ perceptions of AI's importance and the differences between undergraduate and postgraduate students in terms of their understanding and application of AI technologies. The descriptive method was employed, and the sample consisted of 200 undergraduate and 50 postgraduate students from various Iraqi universities. A 31-item questionnaire, divided into two axes. (1) the importance of AI in education and (2) the challenges of its implementation-was distributed during volleyball classes. The results showed that postgraduate students demonstrated a more consistent and logical understanding of AI's educational functions, particularly its flexibility, adaptability, and role in self-directed learning. In contrast, undergraduate students exhibited varied responses, indicating a lack of familiarity with some aspects of AI. Although the postgraduate group had higher mean scores, T-test results showed no statistically significant mean difference (p > 0.05) between the two groups.

The processes of digitalization and digital transformation of the economy have been studied as prerequisites for the development of digital marketing. The main trends in digital marketing and key challenges faced by companies in the process of digital transformation and the use of digital tools have been identified and characterized. The conceptual essence of the terms “digitalization” and “digital transformation” has been deepened, taking into account definitions by both domestic and foreign scholars. It is noted that the process of digital transformation represents a further stage in the development of digitalization through its implementation in the practice of business processes. The expansion of digital marketing capabilities has been shown through the development of modern tools in its various forms: search engine optimization (SEO), content marketing, social media marketing (SMM), email marketing, contextual and targeted advertising (PPC), video marketing, influencer marketing, mobile marketing, voice search, etc. The importance of artificial intelligence in realizing the idea of personalized marketing campaigns that adapt their strategies to consumer demands has been emphasized. Attention has been paid to the security of social networks and combating cybercrime in order to protect customer personal data, minimize financial losses, and prevent reputational damage to companies. Measures to counter cybercrime and prevent unauthorized intrusions into the databases of commercial structures are provided. The most significant digital marketing tools for companies and customers have been identified in terms of solving interaction issues in a market environment. Marketing tools that have a dominant influence on the formation of key marketing strategies of companies have also been defined. The main challenges and issues of digital marketing functioning are described and grouped by areas of their impact: technical and technological, organizational, economic, and ethical, which highlights the importance of finding ways and means of minimizing them. The advantages of an ethical approach to digital marketing have been revealed, as it ensures the formation of a positive company image, corporate social responsibility, and reduces financial, reputational, and other risks.

Artificial Intelligence (AI) has revolutionized medical image analysis, offering advanced tools for disease diagnosis and treatment. This article presents a systematic review of the literature on the applications of AI in quantitative medical image analysis. It discusses the evolution of radiology, the importance of AI in interpreting medical images, and the concepts of Machine Learning, Deep Learning, and Radiomics. The paper explores how AI improves diagnostic accuracy, optimizes workflow, and assists in biomarker identification. Furthermore, challenges and limitations such as data biases, algorithm transparency, ethical and legal issues, implementation costs, and the need for professional training are discussed. It concludes that AI is a powerful complementary tool, but its safe and effective implementtion requires overcoming challenges and robust regulation.

The Purpose of the Study: The importance of artificial intelligence (AI) in design-related education, particularly in interior architecture, has become increasingly significant in today's world. This study aims to explore the integration of AI in furniture design education and its impact on student projects. The primary objective is to evaluate how AI can be incorporated into the design process and how it can enhance students' creative abilities. Conceptual/Theoretical Framework: This research reviews the literature on AI's application in interior architecture and furniture design, highlighting its potential benefits and contributions to current educational methodologies. This study focuses on the "Material and Construction Techniques for Furniture" course, examining how AI-based projects influence students' learning and design outcomes. The study also includes a discussion of the 'text-to-image' literature related to the visual creation technology that the students utilized. Method: The study was conducted with 47 students from the Department of Interior Architecture and Environmental Design at Antalya Bilim University. Students were tasked with redesigning plastic stools into seating elements inspired by selected figures using AI tools. The students were advised to use the artificial intelligence programs MidJourney and DALL-E. In the study, the students' projects were evaluated and graded by a jury. In this context, the projects of students who received 80 points or above were selected. Thus, seven projects were included in the article for detailed analysis. Data were analyzed using qualitative methods to assess students' experiences and learning processes with AI. Findings: The findings indicate that effective use of AI design tools requires a strong foundation in existing design principles; otherwise, the results can be arbitrary. AI tools were most beneficial during the ideation and creative stages. The analysis underscores the transformative potential of AI in traditional design education through innovative methodologies and the promotion of interdisciplinary skills. Clear and guided instruction is crucial for maximizing AI's effectiveness in an educational setting. Conclusion: This study provides valuable insights into the application of AI in design education and suggests that AI-generated imagery can add practical value to the ideation process. The findings highlight key considerations for educators and researchers when integrating AI into design education.

Computational Neuroscience (CN) is an interdisciplinary field that combines neuroscience, mathematics, artificial intelligence, theoretical models and experimental data to understand how the brain works. It unravels the intricacies of the nervous system contributing significantly to cognitive science, neuroengineering and machine learning. CN importance in artificial intelligence and medical research remains underrepresented in Africa's academic landscape. This paper explores the current state of CN in Africa, the challenges hindering its integration, the emerging opportunities, and the evidence-based strategies for curriculum implementation. Capacity building, interdisciplinary collaboration, open science, theoretical neuroscience, development of local capacity, and leveraging international partnerships are emphasized.

This study aims to explore the role of artificial intelligence in developing critical thinking skills, creative thinking, and enhancing entrepreneurship among school students in the Sultanate of Oman from the perspective of life skills teachers. The study stems from the national directions of Oman Vision 2040, which places innovation and knowledge at the heart of the educational process. The researcher adopted a descriptive analytical approach, using an electronic questionnaire administrated to a purposive sample of 21 teachers. The data was analyzed using the SPSS program. The results showed that artificial intelligence has a notable impact on the development of higher- order thinking skills, as the average teacher evaluations were (4.33), for critical thinking, (4.41) for creative thinking, and (4.52) for entrepreneurship–indicators that reflect a high level of conviction among teachers regarding the importance of artificial intelligence in enhancing the learning environment. There were also no statistically significant differences in the teachers’ evaluations based on gender, qualification, experience, or educational stage, indicating a homogeneity in educational orientations. The study recommended the systematic integration of artificial intelligence into school curricula, training teachers in the use of intelligent design and analysis tools, and preparing stimulating digital learning environments, thereby contributing to the development of an entrepreneurial generation capable of innovation and competition in a rapidly evolving knowledge-based economy.

This study aimed to analyze the impact of integrating digital marketing into international marketing strategies, identifying the factors that contribute to its success and the challenges facing companies in global markets. The study adopted the descriptive-analytical approach using the systematic review method by analyzing (26) Arab and foreign studies, and the results showed that 85% of the studies confirmed the integration of digital marketing with international marketing strategies provides companies with a competitive advantage, provided that cultural and technical challenges are taken into account to achieve success in diverse markets. The results of the study found that the integration between digital marketing and international marketing strategies provides companies with a competitive advantage, provided that cultural and technical challenges are taken into account to achieve success in diverse markets. The results also showed that 85% of studies confirmed that digital marketing enhances the efficiency of international marketing strategies, where social media is the most effective in reaching a global audience by 77%, and 54% of studies indicated the importance of artificial intelligence in personalizing content and analyzing data to improve targeting.. Despite the benefits, companies face several challenges, most notably cultural differences (80%) and the technology gap in emerging markets (65%), which hinder the implementation of unified digital strategies. The study recommends the need to customise content according to local cultures, invest in digital infrastructure, and enhance the use of analytical tools to improve marketing performance

The importance of Artificial Intelligence (AI) in modern times cannot be overstated, as it has become a transformative force across nearly every aspect of society. AI is playing an increasingly important role in education, transforming traditional methods of teaching and learning toward more personalized, adaptive approaches. This paper offers an in-depth examination of AI in the educational sector, highlighting the importance of personalized learning and the role of educational technology. AI-enhanced personalized learning utilizes advanced technologies to customize educational content for each student. By adjusting the pacing of lessons, AI ensures that students learn at a speed that suits their individual progress. It provides real-time feedback tailored to the unique needs, preferences, and cognitive abilities of each learner, enhancing their overall educational experience. This transformation holds great promise in significantly enhancing student engagement. By providing personalized content and immediate feedback, it encourages deeper involvement, motivating students to take an active role in their education. Additionally, this shift has the potential to improve academic performance by addressing individual learning needs. Ultimately, AI-powered personalized learning systems foster a more engaging, adaptive, and efficient educational environment. However, the widespread implementation of AI in education presents challenges, including ethical concerns. This paper explores the potential benefits and challenges of AI-powered personalized learning systems, emphasizing the need for guidelines for responsible AI implementation in education. The findings suggest that with careful planning and ethical consideration, AI can significantly enhance educational outcomes, offering a more inclusive and effective learning environment for diverse student populations.

Abstract With the way enterprise networks are changing with high cloud adoption rates, remote working populations and advanced forms of cyber threats, the traditional perimeter approach to security is no longer tenable. Zero Trust Architecture (ZTA) has become an innovative approach to cybersecurity that aims to overcome the weaknesses of the legacy systems due to the implementation of the set of principles of never trust, always verify. This paper will examine the theoretical backgrounds, essential elements, practical applications of ZTA in current business spheres. It offers a critical analysis of existing constructs, including NIST SP 800-207 and the Forrester ZTX framework as well as case studies in the industry, featuring Google BeyondCorp, the Zero Trust implementation at Microsoft, and the Zero Trust requirements at U.S federal government agencies. The comparative analysis used in the study provides both positive points, e.g. the improvement of access control, regulatory compliance, and threat mitigation, and negative ones, e.g. the need to integrate with the legacy infrastructure, the performance overhead, and organizational readiness. Lastly, the article suggests future directions and emerging trends such as the importance of artificial intelligence, blockchain-based identity, and deployment of Zero Trust in Internet of Things (IoT) as well as hybrid cloud ecosystem. Combining the learning of the scholarly world and the practices of organizations, this paper will provide an enterprise with a clear guide on how to implement Zero Trust without limits, vulnerability, and cognizance.

In the last decade, debates on digitalization programs and on dynamics of datafication have become increasingly influential at universities. More recently, debates on the importance of artificial intelligence (AI) have begun, although corresponding questions about changing knowledge ecologies are currently underexplored in educational research. The processes of changing knowledge production are encountering relatively entrenched structures of knowledge organization and communication at universities, which are struggling to handle these new challenges. In this paper we use the historically-shaped university organization structures in three European countries as cases of analysis. Thus, first we give an overview of the concepts of knowledge ecology and knowledge diversity, followed by, second, a critical discussion of current trends in the digitalization and datafication of scientific knowledge production in education with examples from Italy, Austria and Germany, The choice of these different and highly complex scientific systems is justified by our experiences in these diverse contexts and corresponding academic affiliations. Third, we reflect on the implications of changing knowledge ecologies and knowledge diversity for the future of higher education.