Systematic review - innovative approaches in artificial intelligence development

In recent years, due to the rapid development of artificial intelligence (AI) and machine learning, its application has been widely used in many aspects of financial area, as well as significantly impacts financial market, institutions and regulation. The artificial intelligence technology brings enormous change to the entire financial industry, which creates a series of innovative financial services such as intelligent consultant, intelligent lending, monitoring and warning, and intelligent customer service as times required. In this paper, it aims to summarize the development and application of artificial intelligence and machine learning in financial system, as well as its impacts on macroeconomics and microeconomics. In the meantime, it is realised that a series of problems and risks were conducted by artificial intelligence during its use. Lastly, some suggestions and strategies are provided for reasonable usage of artificial intelligence in financial risk management, based on the financial risk management raised by artificial intelligence.

Purpose This study analyzes China’s strategic initiatives in metaverse and artificial intelligence (AI) development, examining their impact on academic research, industry innovation, and policy formulation. It aims to understand how government policies and investments have shaped research agendas and to identify challenges and opportunities in these fields. Design/methodology/approach The research employs a comprehensive analysis of government documents, funding schemes, and research output. It examines key policies, investment programs, and academic publications to track trends in metaverse and AI development in China. The study utilizes bibliometric analysis to assess publication trends, citation patterns, and international collaboration networks. Findings China’s proactive approach, characterized by strong government support and significant private sector investment, has led to a substantial increase in research output and quality in metaverse and AI fields. Chinese institutions have become major contributors to global publications, with growing citation rates and presence at international conferences. The research identifies emerging challenges in privacy, ethical AI development, and digital divide concerns. Practical implications The findings provide insights for policymakers, researchers, and industry stakeholders on the development trajectory of metaverse and AI technologies in China. They highlight the need for balanced approaches to innovation, regulation, and ethical considerations in these rapidly evolving fields. Social implications The study underscores the potential of metaverse and AI technologies to transform various sectors of society, from education and healthcare to entertainment and social interactions. It emphasizes the importance of addressing digital equity and ethical AI deployment to ensure broad societal benefits. Originality/value This research offers a comprehensive overview of China’s approach to metaverse and AI development, providing a unique perspective on the interplay between government initiatives, academic research, and industry innovation. It contributes to the broader discussion on the global development of these transformative technologies and their implications for future technological landscapes.

Artificial Intelligence (AI) has rapidly emerged as a transformative force in modern medicine, revolutionising diagnostics, treatment personalisation, and clinical decision-making. This review synthesises current literature on AI's evolution, applications, challenges, and future directions in healthcare. From early rule-based systems to advanced deep learning algorithms, AI has consistently demonstrated capabilities that rival and enhance human expertise—particularly in imaging, predictive analytics, and drug discovery. The role of AI in global health is also expanding, offering scalable solutions to reduce disparities in low-resource settings. However, the integration of AI raises ethical and legal concerns, including data privacy, algorithmic bias, and unclear accountability frameworks. Drawing on the Technology Acceptance Model (TAM), Diffusion of Innovations Theory, and Principlism, this review highlights theoretical perspectives essential to understanding AI adoption and governance. The paper concludes with a call for longitudinal studies, ethical frameworks, and policy innovations to support AI's responsible and equitable deployment in the medical field.

In the last few years, with the rapid development of artificial intelligence (AI) technology, its application in the medical field has become more and more in-depth and extensive, especially the research of computer vision technology in medical image analysis and recognition has achieved many results. It is recognized by experts engaged in imaging diagnosis in the medical field, which has provided a great boost to the development of precision medicine. However, the application and development of artificial intelligence in the field of medical imaging is still in its infancy, and faces many technical and ethical challenges, such as data quality issues, data security issues and clinical application issues. The application of AI technology in medical imaging needs to be further adjusted and improved in combination with social development and actual needs. In this paper, we discussed the usages of artificial intelligence in medical imaging and provided new sights for the sustainable development and improvement in this area, as well as the challenges faced by others.

Globalisation of the strategy for the development and implementation of artificial intelligence (AI) in Ukraine and/or deepening the direction in nominal areas of social life, i.e. individuals in society, respectively, in the fields of art, design, medicine, commercial activity, science and education, banking and deep military and national strategy and national security in cadence formats such as ChatGPT, i.e: • Artificial intelligence – AI; • Artificial Neural Networks – ANN – computing systems. The dynamic position in the context of the emergence of artificial intelligence (AI) and its further application in the educational process in relation to the first stage, i.e. the species concept on the part of educators and students of education from among the convicts in the status of a special contingent, respectively, was remade in relation to the nominal field of vocational training in the context of penitentiary education, In other words, artificial intelligence (AI) in the form of a contact line requested a penitentiary trajectory for the format of the social and creative model teacher-education student from among prisoners in the status of a special contingent. Accordingly, the special contingent in the form of students from the prison population in the status of a special contingent needs to be fluent in digital technologies in accordance with the requirements of modern society, to improve and enhance the nominal abilities that will be needed for further employment in the digital world. The motivation of the present regarding the project perspective of artificial intelligence (AI) in penitentiary education in the status of a special contingent, that is, the involvement of the social and creative model of teacher-educator from among the convicts of imprisonment in the status of a special contingent is characterized by the intense development of artificial intelligence (AI) technologies and the introduction of. The generation of the relationship between artificial intelligence (AI) and education goes beyond the application of artificial intelligence (AI) during the acquisition of theoretical training, i.e., taking into account the study of artificial intelligence (AI) technologies and the professional training of students from among prisoners of imprisonment in the status of a special contingent within the framework of penitentiary education.

This paper explains the ethical implications of artificial intelligence (AI) development towards achieving the level of artificial general intelligence (AGI) and analyzes the need for its social control. With the acceleration and intensification of AI growth and development, especially with the ongoing AI race, the transition from narrow AI to AGI becomes certain. The achievement of generative AI, which climaxes with chatbots (such as ChatGPT and others), transforms AI into a machine capable of creation. Although this AI application still appears relatively limited by algorithms, its learning ability is remarkable, and continuous advancements and the launch of increasingly sophisticated versions bring it ever closer to the AGI model. Each day brings us closer to that moment, which will signify AI’s transition from narrow AI to AGI. Unlike narrow AI, AGI deeply delves into the realm of ethics, and interpersonal and social relationships. Regulating AI-related policy and legally controlling AI represents one of the most serious and complex issues. In recent years, the community, led by corporate executives developing AI, prominent experts, researchers, scientists, writers, and other stakeholders, has made significant steps towards raising public awareness of the risks posed by advanced AI and making decisions, initiatives, and measures for monitoring, analyzing, and socially controlling the use of AI.

A national survey on how to improve the integration of traditional Chinese medicine and artificial intelligence: Attitudes and perceptions from medical staff.

This article provides a brief overview of the application and development of artificial intelligence (AI) in the field of education under the background of New Liberal Arts. It also highlights the importance and current status of innovative approaches in college English teaching. Furthermore, it presents the research objectives and methods. The application of artificial intelligence in education has witnessed significant growth and advancement in recent years. AI technologies, such as machine learning and natural language processing, have been utilized to enhance various aspects of education, including personalized learning, intelligent tutoring systems, and automated grading. These applications have shown promising results in improving students' learning outcomes and engagement. In the context of college English teaching, innovation is crucial to meet the evolving needs and expectations of students. Traditional teaching methods often fail to cater to individual learning styles and preferences, leading to limited effectiveness and student disengagement. Therefore, there is a pressing need to explore innovative approaches that leverage AI technologies to create more interactive and personalized learning experiences. The research aims to investigate the potential of integrating AI into college English teaching and its impact on students' learning outcomes and engagement. The study will employ a mixed-methods approach, combining quantitative analysis of students' performance data with qualitative interviews and surveys to gather comprehensive insights. By examining the effectiveness and challenges of AI integration in English teaching, this research seeks to provide valuable recommendations for educators and policymakers to enhance the quality of college English education. Above all , this study aims to explore the application of artificial intelligence in college English teaching, considering its potential to improve learning outcomes and engagement. By adopting a mixed-methods research approach, this study intends to provide valuable insights and recommendations for educators and policymakers to promote innovative and effective English teaching practices.

The rate of development in artificial intelligence (AI) technologies has brought revolutionary transformationsacross the healthcare sector. The advancements especially impacted the manner in which the diagnosis,treatment, and management of diseases are undertaken with a growing emphasis laid on optimizing clinicalworkflow and patient care. Machine learning (ML) and deep learning (DL) technologies have proved invaluablefor the analysis of complex datasets, supporting early diagnosis and optimizing treatment protocols. AIshowcased tremendous promise in a plethora of applications, such as the accurate analysis of medical imagery,the personalization of therapies through the tailor-made dosing of medicines, predictive analysis in forecastingthe course of the disease, and the assistance of patients and clinicians by deploying virtual health tools.Moreover, the increasing application of AI in healthcare has also boosted access to quality healthcare,particularly in underserved populations. The following review also explores the ethical, legislative, andregulatory issues related to the application of AI in medicine, reiterating the need for protection of the data,transparency, and equitable access. With careful implementation that respects these boundaries, AI holds thepotential to significantly enhance global healthcare delivery. Despite these benefits, integrating AI intohealthcare systems raises important ethical, legal, and regulatory concerns. Ensuring data privacy, promotingalgorithm transparency, and maintaining fairness in AI-driven healthcare solutions are key concerns.Addressing these challenges is vital to building trust and ensuring that AI technologies benefit all populationsfairly. With responsible and ethical implementation, AI holds immense potential to transform global healthcaredelivery and improve patient outcomes on a large scale. How to cite this: Jan TA, Naz S. Artificial Intelligence in Medicine: Transforming The Future of Healthcare. Life and Science. 2025; 6(2): 284-291. doi: http://doi.org/10.37185/LnS.1.1.904

Follow-up of Artificial Intelligence Development and its Controlled Contribution to the Article: Step to the Authorship?

BackgroundDespite the extensive hopes and expectations for value creation resulting from the implementation of artificial intelligence (AI) applications in healthcare, research has predominantly been technology-centric rather than focused on the many changes that are required in clinical practice for the technology to be successfully implemented. The importance of leaders in the successful implementation of innovations in healthcare is well recognised, yet their perspectives on the specific innovation characteristics of AI are still unknown. The aim of this study was therefore to explore the perceptions of leaders in healthcare concerning the innovation characteristics of AI intended to be implemented into their organisation.MethodsThe study had a deductive qualitative design, using constructs from the innovation domain in the Consolidated Framework for Implementation Research (CFIR). Interviews were conducted with 26 leaders in healthcare.ResultsParticipants perceived that AI could provide relative advantages when it came to care management, supporting clinical decisions, and the early detection of disease and risk of disease. The development of AI in the organisation itself was perceived as the main current innovation source. The evidence base behind AI technology was questioned, in relation to its transparency, potential quality improvement, and safety risks. Although the participants acknowledged AI to be superior to human action in terms of effectiveness and precision in some situations, they also expressed uncertainty about the adaptability and trialability of AI. Complexities such as the characteristics of the technology, the lack of conceptual consensus about AI, and the need for a variety of implementation strategies to accomplish transformative change in practice were identified, as were uncertainties about the costs involved in AI implementation.ConclusionHealthcare leaders not only saw potential in the technology and its use in practice, but also felt that AI’s opacity limits its evidence strength and that complexities in relation to AI itself and its implementation influence its current use in healthcare practice. More research is needed based on actual experiences using AI applications in real-world situations and their impact on clinical practice. New theories, models, and frameworks may need to be developed to meet challenges related to the implementation of AI in healthcare.

This article is dedicated to identifying the fundamental differences between artificial intelligence and machine learning. The aim of the research is to analyze, systematize, and improve the existing theoretical and methodological framework concerning the functioning of artificial intelligence and machine learning, as well as to define the distinctions between these systems. The article examines the current state and prospects for the development of artificial intelligence and machine learning as integral components of innovative technologies that facilitate the automation of complex processes and enhance efficiency across various fields. The research outlines the main stages in the development of artificial intelligence: weak artificial intelligence, which specializes in performing narrow tasks; strong artificial intelligence, aimed at achieving human cognitive capabilities; and superintelligence, which is expected to surpass human intelligence in many aspects. The study substantiates the role of machine learning as a key tool for implementing artificial intelligence, enabling the creation of systems that can self-learn and adapt to changing conditions without additional programming. The article provides examples of the application of artificial intelligence and machine learning in various sectors such as medicine, finance, cybersecurity, marketing, and transportation, where these technologies contribute to improving diagnostic processes, forecasting market fluctuations, and optimizing decision-making. In particular, the main advantages of machine learning are identified, including adaptability and the ability to make predictions based on large data sets, which enhances the effectiveness of analysis and decision-making in real time. The research into the development of artificial intelligence has revealed the technical and ethical challenges associated with creating strong artificial intelligence and superintelligence, which require the development of appropriate regulatory measures. The article emphasizes the significance of artificial intelligence and machine learning for modern society, their impact on various fields of economics, science, and technology, as well as the necessity for further research to ensure the safe and effective development of these technologies.

The development of Artificial Intelligence (AI) technology has a significant impact on various sectors, including education. One interesting application of AI is Text to Questions, a technology that converts narrative text into questions for automatic question creation. ANDALIMAN is a Moodle-based Learning Management System developed by the Religious Training Center (BDK) Medan, a platform designed for training management, including material management, teaching resources, assessments, and the creation and questions management. AI in the ANDALIMAN is expected to improve efficiency and produce a greater variety of questions in less time. The implementation of AI also demonstrates excellent potential to enhance the quality of learning assessments, although it faces challenges in generating accurate questions that meet specific training needs. This research aims to explore the application of AI technology in the ANDALIMAN application, focusing on its impact on question quality, question creation time, and the advantages/disadvantages of that technology. The research results indicate that the efficiency and quality of quiz creation have improved, as evidenced by time efficiency and increased productivity, making it a practical solution, particularly in education. Abstrak Kemajuan teknologi Artificial Intelligence (AI) memberikan dampak signifikan dalam berbagai sektor, termasuk pendidikan. Salah satu penerapan AI yang menarik adalah Text to Questions, yaitu teknologi yang mampu mengonversi teks naratif menjadi pertanyaan untuk pembuatan soal secara otomatis. ANDALIMAN (Aplikasi Pendukung Pelatihan BDK Medan) merupakan aplikasi yang dikembangkan oleh Balai Diklat Keagamaan (BDK) Medan berbasis Learning Management System (LMS) Moodle, sebuah platform yang dirancang untuk pengelolaan pelatihan, baik mulai dari pengelolaan materi, bahan ajar, penilaian, hingga pembuatan dan pengelolaan soal. Penggunaan AI dalam Aplikasi ANDALIMAN diharapkan dapat meningkatkan efisiensi dan menghasilkan soal dengan variasi yang lebih banyak dalam waktu yang lebih singkat. Penerapan AI juga menunjukkan potensi besar untuk meningkatkan kualitas evaluasi pembelajaran, namun dihadapkan dengan tantangan dalam menghasilkan soal yang akurat dan sesuai dengan kebutuhan spesifik pelatihan. Penelitian ini bertujuan untuk mengeksplorasi penerapan teknologi AI dalam aplikasi ANDALIMAN, dengan fokus pada dampaknya terhadap kualitas soal, waktu pembuatan soal, dan kelebihan/kekurangan pada teknologi tersebut. Hasil riset menunjukkan bahwa efisiensi dan kualitas pembuatan soal kuis menjadi meningkat dilihat dari efisiensi waktu dan peningkatan produktifitas yang dapat menjadi solusi efektif khususnya dalam bidang pendidikan.

This study examined artificial intelligence (AI) applications for health information service delivery throughout Africa and its subregions. The study aimed to review existing research, identify key AI applications in healthcare, assess their impact in African healthcare, and examine strategies that promote effective, ethical, and equitable integration for sustainable healthcare improvements across the continent. African healthcare systems face obstacles, including restricted access to quality information, shortages of healthcare professionals, and infrastructural limitations. AI presents promising solutions to these challenges. The article comprises a systematic literature review of peer-reviewed research on AI-driven health information service delivery in Africa between 2014 and 2024, examining key AI applications, opportunities, challenges, and ethical considerations associated with AI adoption in healthcare, and their influence on health information service delivery. This review examined African healthcare systems’ preparedness for AI adoption, the importance of digital literacy, and the infrastructure that affects AI dissemination. The study also examined ethical considerations, including data privacy, equity, and the risk of widening health disparities. The findings reveal that AI technologies can enhance the accessibility, precision, and efficiency of health information services across Africa, particularly in underserved areas. The primary obstacles to AI adoption include insufficient digital infrastructure, low digital literacy, and socio-cultural hurdles. This review emphasises addressing ethical concerns to ensure that AI-driven health information systems benefit all populations without exacerbating inequality. The review offers insights for policymakers, healthcare providers, and researchers. Areas for future research and development were reviewed to ensure sustainable and equitable AI integration across Africa’s healthcare systems. The study recommends that stakeholders invest in digital infrastructure, promote digital literacy, and establish ethical guidelines for successful and equitable AI integration into health information service delivery throughout Africa.

The development of artificial intelligence (AI) technology is often seen as the domain of engineers, but ultimately, it is the everyday consumer who uses it. This means that AI is not just an engineering challenge; it must also be understood from the perspectives of marketing and consumer behavior. In this study, we first use the CiteSpace knowledge mapping tool to analyze research trends and their evolution in the field of AI from a macro perspective. Then, from a micro perspective, we carefully select and review key literature to define the concept of AI, and further provide a comprehensive overview of AI applications in marketing. This includes (1) AI technology and product acceptance factors, (2) Algorithm avoiding and doubts about AI, (3) Industry-spcific application of AI, and (4) Consumer behavior and psychological on AI. Finally, based on existing research findings, we propose future research topics and directions that are necessary for the continued exploration of AI in this context. The insights from this study can inspire new research ideas related to AI for marketing and consumer scholars. Furthermore, it offers an opportunity for business marketers and government policymakers to consider AI not just as a technological issue, but from the perspective of the consumers who will ultimately adopt and interact with these technologies.