The Role of Artificial Intelligence in Theranostics.

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.

Fatty liver disease, also known as hepatic steatosis, poses a significant global health concern due to the excessive accumulation of fat within the liver. If left untreated, this condition can give rise to severe complications. Recent advances in artificial intelligence (AI, specifically AI-based ultrasound imaging) offer promising tools for diagnosing this condition. This review endeavors to explore the current state of research concerning AI's role in diagnosing fatty liver disease, with a particular emphasis on imaging methods. To this end, a comprehensive search was conducted across electronic databases, including Google Scholar and Embase, to identify relevant studies published between January 2010 and May 2023, with keywords such as "fatty liver disease" and "artificial intelligence (AI)." The article selection process adhered to the PRISMA framework, ultimately resulting in the inclusion of 13 studies. These studies leveraged AI-assisted ultrasound due to its accessibility and cost-effectiveness, and they hailed from diverse countries, including India, China, Singapore, the United States, Egypt, Iran, Poland, Malaysia, and Korea. These studies employed a variety of AI classifiers, such as support vector machines, convolutional neural networks, multilayer perceptron, fuzzy Sugeno, and probabilistic neural networks, all of which demonstrated a remarkable level of precision. Notably, one study even achieved a diagnostic accuracy rate of 100%, underscoring AI's potential in diagnosing fatty liver disease. Nevertheless, the review acknowledged certain limitations within the included studies, with the majority featuring relatively small sample sizes, often encompassing fewer than 100 patients. Additionally, the variability in AI algorithms and imaging techniques added complexity to the comparative analysis. In conclusion, this review emphasizes the potential of AI in enhancing the diagnosis and management of fatty liver disease through advanced imaging techniques. Future research endeavors should prioritize the execution of large-scale studies that employ standardized AI algorithms and imaging techniques to validate AI's utility in diagnosing this prevalent health condition.

This study investigates how generative artificial intelligence (AI) could influence the media environment of that country. Given their prevalence in the industry, it seeks to uncover how general process of national advancement is supported by AI-powered technologies in media content generation, distribution, and personalisation. The research gathers data from media professionals, techies, and communication academics in major Chinese cities all around using properly crafted questionnaires in a quantitative manner. One examined the interactions of AI-driven media innovation, modernising pace, and consequences of national development using statistical methods like structural equation modelling and regression analysis. Linking modernism with national development projects, the indices of generative AI used in media show a definite positive link with their influence. Generative AI is becoming more and more important for China's attempts to modernise its communication infrastructure and undergo digital transformation, thereby enhancing the nation's cultural impact, technical capacity, and media creation. Modernism approaches enhance the possibilities presented by AI in media; this research reveals more dynamic storylines, audience interaction feasible, and global outreach. Every one of these components helps to forward objectives for national growth. Regarding developing plans to mix AI with goals for sustainable development, the findings give legislators, media outlets, and AI developers’ useful insights. This study offers a structure for further studies in new media technologies and national transformation by means of an experimental interaction between generative AI and national development seen from the perspective of modernism. It opens the conversation on the social opportunities AI offers.

The article presents the results of the study conducted by the author in the field of sovereign social ecology using artificial intelligence technologies. The issues of social ecology implemented on the basis of strategic programs and national projects are considered. A number of environmental programs aimed at protecting the environment and stimulating sustainable development are shown. The role of artificial intelligence (AI) in solving issues of social ecology, which is carried out through environmental monitoring, natural resource management and environmental education, is determined. The key aspects of the use of artificial intelligence (AI) technologies when they are implemented in certain areas of activity are identified. The role of generative artificial intelligence (GAI) in the implementation of social ecology technologies is shown, examples of the use of generative AI in this area are given. The prospects for the implementation of social ecology technologies in Russia and the world are shown.

In this paper, the application of Artificial intelligence (AI) methods in power system protection and inspection has been discussed. In this paper particularly AI application of line scout Robot is used. Line scout robot is an inspection based Artificial intelligence Robot. Line Scout robot is able to work on the power lines while they are operating (at very high tension). The robot can patrol in a substation and inspect equipment with a visible-light camera and thermograph. It has possess a vast array of cameras and tools that allow the remote operators to inspect and conduct (albeit minor) repairs on the power lines without needing to put the off-service or risking their lives. It is preventive arrangement for detection of fault (very high temperature). Keywords: Artificial intelligence (AI), artificial general intelligence (AGI), corona pulse, Line Scout Robot, power system

Human resources (HR) experts can now utilize calculations and AI to smooth out their work processes, diminish their predispositions, and work on their examination and dynamic on account of advancements in artificial intelligence (computer based intelligence) innovation. Nonetheless, a few organizations are reluctant to embrace computer based intelligence for extra use cases because of the ongoing downsides and weaknesses. In human resource management, artificial intelligence (computer based intelligence) can be extremely helpful on the grounds that it can robotize drawn-out assignments and diminish predisposition in the determination cycle. Man-made intelligence can be applied to progress authoritative procedures, improve employee engagement, and support vocation development. Employee engagement can be expanded and vocation useful learning experiences can be more individualized and custom-made with the guide of computer based intelligence innovation. The monetary expenses of setting up and maintaining artificial intelligence in HR, as well as the risk of missteps and unintentional predispositions, ought to be considered by associations. Future advancements in artificial intelligence will expand personalization, mechanization, and data based decisions in human resource management. Before very long, as artificial intelligence keeps on changing the scene of human resource management, HR managers should likewise know about the challenges they might experience. Worries about simulated intelligence making work more secure and more open are normal among HR chiefs. The recruiting and preparing of new employees is a dreary undertaking for the department of human resources. Artificial intelligence has many applications that can assist with peopling who work in human resources with their manual work. Hence, the present study has been focused to give a theoretical outline on the role of Artificial Intelligence (AI) in Human Resource Management (HRM) in recent era.

This study explores the impact of artificial intelligence (AI) on the growth and competitiveness of regional tourism and hospitality destinations. AI's application has both positive and negative effects on sustainable tourism. On the positive side, AI enhances accessibility to tourist sites, provides detailed information about attractions, simplifies understanding of costs and amenities, boosts local economies, and increases federal income. A notable downside is the replacement of human workers by machine learning technologies, which may necessitate remedial measures such as training. This review examines AI's foundational IT principles, current applications, and systems in the industry, focusing on the hotel sector. It concludes with an overview of AI’s challenges in this field, proposes a research agenda, and suggests future directions for AI development in tourism and hospitality.

Artificial Intelligence (AI) is rapidly transforming the field of nuclear medicine, offering novel ways to enhance diagnostic accuracy, treatment planning, and patient outcomes. This chapter explores the current applications of AI in nuclear medicine, highlighting its role in imaging, radiomics, and personalized therapy. AI-driven algorithms are increasingly utilized to optimize the processing and interpretation of nuclear imaging modalities such as Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT). Machine learning and deep learning techniques are enabling more precise detection of diseases, including cancer, neurological disorders, and cardiovascular conditions, by analyzing complex patterns in imaging data that are often overlooked by human radiologists. AI is improving dosimetry and treatment planning in theranostics, enabling more effective, patient-specific radiotherapy. It focuses on integration of AI in multi-disciplinary care, focusing on the synergy between AI systems, clinicians, and other healthcare technologies.

The present study investigates the potential impact of artificial intelligence (AI) on the future trajectory of human civilization. It focuses on topics such as super-exponential growth, the potential emergence of a galactic civilization, and the associated "doom" hazards. A significant advancement in machine intelligence with human-like consciousness, strong artificial intelligence (AI), also known as artificial general intelligence (AGI), creates new opportunities and capacities. There's growing anxiety about the risk that weak AI will eventually become strong AI. Every year, new transformer models that are more like human interactions are being created, and we have already witnessed some indications of AGI. It is anticipated that AI will reach a "singularity" and advance on its own without assistance from humans. This thesis explores the theoretical and practical foundations, model building blocks, development processes, challenges, and ethical issues surrounding the creation of Consciousness AI (AGI). This paper examines the meaning of the term "technological singularity," the various types of singularities that have no point of return idea, the philosophical risks associated with the development of AI, and the implications of AI singularity for monetary theory and the new economic order. As a new perspective on the deployment of ethical AI in the face of tremendous technological advancements, the study not only contributes to the theoretical discourse but also explores the possible practical implications of AI on our shared future. Several obstacles to AI advancement are covered in the paper, along with prospective directions for future research.

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.

Artificial intelligence has provided great potential and space for the optimization of electrical engineering and it will bring about great improvement not only in economic aspect but also in safety and actual operation control. Since the advent of artificial intelligence it has been widely applied in all fields of life and achieved notable application effect its emergence has even pointed out the direction for the development of many fields and the field of electrical automation control is no exception. In reality, the application of artificial intelligence technology has greatly promoted the progress of the concrete practice of electrical automation and should be paid full attention to by related enterprises and staff. This paper aims to summarize the emergence and development of artificial intelligence and its components and finally summarize the advantages and functions of artificial intelligence in electrical automation control. Advances in machine learning and artificial intelligence (AI) techniques bring new opportunities to numerous intractable tasks for operation and control in modern electric distribution systems. Revolving around the characteristics of distribution system operation and integration of distributed energy resources this paper also illuminates prospects and challenges typified by the privacy explain ability and interpretability of such AI applications in smart grids. KEYWORDS: - Distribution systems, smart buildings, neural networks, Artificial Intelligence, Electrical Engineering, power systems.

Recent developments in artificial intelligence (AI) have stimulated considerable excitement and discussion regarding the potential impacts on people's lives and work. In particular, proposed and realized applications of generative AI have appeared across multiple industries and domains, including at the intersection of behavioral science and the law. This manuscript presents an ethical analysis of applications of generative AI to violence risk assessment, guided by the ethical principles of autonomy, beneficence and non-maleficence, and justice. The authors argue that generative AI, although capable of producing novel content, is nonetheless vulnerable to ethical problems, including through its exposure to biased training data. Issues such as limited transparency in decision making and the potential for the perpetuation and exacerbation of racial disparities are discussed. The authors recommend that professionals approach generative AI with due caution, as they would with any novel or emerging risk assessment approach, and suggest continued evaluation and research.

Among the evaluation indicators of national development level, the degree of power system development is one of the important indicators. Economic and social needs have gradually expanded the scale of the power grid, and many distributed renewable energy sources are continuously connected to the power grid system, making the power system more and more complex; the data generated during the application of the power system presents typical big data characteristics, such as presenting large, heterogeneous, and multi-source characteristics. Faced with the new characteristics of power data, the requirements for methods of analyzing and processing power data problems have increased. The current research on artificial intelligence (AI) in the computer field is getting deeper and deeper, and the application of AI in various industries has made greater research progress. It is the key to future scientific and technological progress. In my country’s development strategy, it is clearly required to promote the development of AI and regard the power system as one of the main application areas of AI. The rapid development and advancement of artificial intelligence can provide powerful tools in many aspects of the power system, including power system planning and design, coordinated control, simulation, prediction and estimation, diagnosis and identification. This article first analyzes the artificial intelligence technology, introduces the two mainstream artificial intelligence technologies in the current situation, and analyzes the power system, and then studies and analyzes the application of artificial intelligence technology in the electrical system.

The policy of military neutrality is one of the fundamental principles of the contemporary foreign and security policy of the Republic of Serbia. In the era of artificial intelligence, this concept gains a new dimension, technological neutrality as a condition for strategic autonomy. The development and application of artificial intelligence not only affect military capabilities, but also shape power relations, economic dependence and cognitive control within the global system. In such a context, the issue of neutrality no longer refers exclusively to military alliances, but to the ability of a state to manage its own digital sovereignty and maintain a balance between different technological spheres of influence. Military alliances can and should be considered in the context of neutrality, but not as membership, but as a reference framework of strategic orientation and limitations. The paper starts from the assumption that artificial intelligence is becoming an important factor in defining new forms of strategic dependence and resilience. Serbia, positioned between Western and Eastern technological systems, faces the challenge of extending its neutrality into the domain of algorithmic policy and digital infrastructure. Instead of bloc alignment, artificial intelligence can become an instrument of intelligent balancing, a means by which the state strengthens its own analytical, communication and security capacities, while maintaining control over data and processes of national importance. In conclusion, the paper proposes the concept of "intelligent neutrality", which implies the integration of the principles of digital sovereignty, ethical responsibility and technological independence of Serbia. This model can serve as a theoretical and practical basis for the development of a new type of neutrality in the digital era, a neutrality that does not rest on isolation, but on the active control of algorithmic power flows. Serbia thus has the opportunity to become an example of an adaptive state that not only resists the influences of great powers, but also shapes its own digital identity within a multipolar order.

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.