Predictive algorithms in healthcare: constituting ‘Artificial Intelligence’ (AI) as near human

PurposeThis study aims to show the inconsistency of the approach to the development of artificial intelligence as an independent tool (just one more tool that humans have developed); to describe the logic and concept of intelligence development regardless of its substrate: a human or a machine and to prove that the co-evolutionary hybridization of the machine and human intelligence will make it possible to reach a solution for the problems inaccessible to humanity so far (global climate monitoring and control, pandemics, etc.).Design/methodology/approachThe global trend for artificial intelligence development (has been) was set during the Dartmouth seminar in 1956. The main goal was to define characteristics and research directions for artificial intelligence comparable to or even outperforming human intelligence. It should be able to acquire and create new knowledge in a highly uncertain dynamic environment (the real-world environment is an example) and apply that knowledge to solving practical problems. Nowadays artificial intelligence overperforms human abilities (playing games, speech recognition, search, art generation, extracting patterns from data etc.), but all these examples show that developers have come to a dead end. Narrow artificial intelligence has no connection to real human intelligence and even cannot be successfully used in many cases due to lack of transparency, explainability, computational ineffectiveness and many other limits. A strong artificial intelligence development model can be discussed unrelated to the substrate development of intelligence and its general properties that are inherent in this development. Only then it is to be clarified which part of cognitive functions can be transferred to an artificial medium. The process of development of intelligence (as mutual development (co-development) of human and artificial intelligence) should correspond to the property of increasing cognitive interoperability. The degree of cognitive interoperability is arranged in the same way as the method of measuring the strength of intelligence. It is stronger if knowledge can be transferred between different domains on a higher level of abstraction (Chollet, 2018).FindingsThe key factors behind the development of hybrid intelligence are interoperability – the ability to create a common ontology in the context of the problem being solved, plan and carry out joint activities; co-evolution – ensuring the growth of aggregate intellectual ability without the loss of subjectness by each of the substrates (human, machine). The rate of co-evolution depends on the rate of knowledge interchange and the manufacturability of this process.Research limitations/implicationsResistance to the idea of developing co-evolutionary hybrid intelligence can be expected from agents and developers who have bet on and invested in data-driven artificial intelligence and machine learning.Practical implicationsRevision of the approach to intellectualization through the development of hybrid intelligence methods will help bridge the gap between the developers of specific solutions and those who apply them. Co-evolution of machine intelligence and human intelligence will ensure seamless integration of smart new solutions into the global division of labor and social institutions.Originality/valueThe novelty of the research is connected with a new look at the principles of the development of machine and human intelligence in the co-evolution style. Also new is the statement that the development of intelligence should take place within the framework of integration of the following four domains: global challenges and tasks, concepts (general hybrid intelligence), technologies and products (specific applications that satisfy the needs of the market).

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

The integration of artificial intelligence into the system of higher education represents a turning point in the process of learning and teaching. The development of artificial intelligence has opened the way to personalized training, automation of administrative tasks and the introduction of innovative training methods. The purpose of the study was to analyze the practical aspects of using artificial intelligence in higher education institutions of Ukraine. It was determined that artificial intelligence is an organized set of information technologies, which makes it possible to perform complex complex tasks. There are three main categories of artificial intelligence: narrow-spectrum artificial intelligence, or Artificial Narrow Intelligence, general artificial intelligence, or Artificial General Intelligence, and artificial superintelligence, or Artificial Super Intelligence. The main educational services provided by artificial intelligence in institutions of higher education are the development and conduct of lectures, seminars and practical classes; teacher counseling; creation of educational programs and electronic courses; development of tasks and simulation of their solution; conducting various educational events; evaluation of the works of education seekers. Some examples of the use of artificial intelligence, in particular chatbots, in the higher education of Ukraine are analyzed and their potential for improving the educational process and forming professional skills is emphasized. An example of the use of GPT-3.5 in the Luhansk Educational and Scientific Institute for teaching foreign languages is presented. Such applications based on artificial intelligence as Thinkster and Duolingo and the main aspects of their use by students of higher education are characterized. Recommendations are provided for the successful implementation of artificial intelligence technologies in higher education.

The integration of artificial intelligence into the system of higher education represents a turning point in the process of learning and teaching. The development of artificial intelligence has opened the way to personalized training, automation of administrative tasks and the introduction of innovative training methods. The purpose of the study was to analyze the practical aspects of using artificial intelligence in higher education institutions of Ukraine. It was determined that artificial intelligence is an organized set of information technologies, which makes it possible to perform complex complex tasks. There are three main categories of artificial intelligence: narrow-spectrum artificial intelligence, or Artificial Narrow Intelligence, general artificial intelligence, or Artificial General Intelligence, and artificial superintelligence, or Artificial Super Intelligence. The main educational services provided by artificial intelligence in institutions of higher education are the development and conduct of lectures, seminars and practical classes; teacher counseling; creation of educational programs and electronic courses; development of tasks and simulation of their solution; conducting various educational events; evaluation of the works of education seekers. Some examples of the use of artificial intelligence, in particular chatbots, in the higher education of Ukraine are analyzed and their potential for improving the educational process and forming professional skills is emphasized. An example of the use of GPT-3.5 in the Luhansk Educational and Scientific Institute for teaching foreign languages is presented. Such applications based on artificial intelligence as Thinkster and Duolingo and the main aspects of their use by students of higher education are characterized. Recommendations are provided for the successful implementation of artificial intelligence technologies in higher education.

Historically, the term "artificial intelligence" dates to 1956 when it was first used in a conference at Dartmouth College in the US. Since then, the development of artificial intelligence has in part been shaped by the field of neuroscience. By understanding the human brain, scientists have attempted to build new intelligent machines capable of performing complex tasks akin to humans. Indeed, future research into artificial intelligence will continue to benefit from the study of the human brain. While the development of artificial intelligence algorithms has been fast paced, the actual use of most artificial intelligence (AI) algorithms in biomedical engineering and clinical practice is still markedly below its conceivably broader potentials. This is partly because for any algorithm to be incorporated into existing workflows it has to stand the test of scientific validation, clinical and personal utility, application context, and is equitable as well. In this context, there is much to be gained by combining AI and human intelligence (HI). Harnessing Big Data, computing power and storage capacities, and addressing societal issues emergent from algorithm applications, demand deploying HI in tandem with AI. Very few countries, even economically developed states, lack adequate and critical governance frames to best understand and steer the AI innovation trajectories in health care. Drug discovery and translational pharmaceutical research stand to gain from AI technology provided they are also informed by HI. In this expert review, we analyze the ways in which AI applications are likely to traverse the continuum of life from birth to death, and encompassing not only humans but also all animal, plant, and other living organisms that are increasingly touched by AI. Examples of AI applications include digital health, diagnosis of diseases in newborns, remote monitoring of health by smart devices, real-time Big Data analytics for prompt diagnosis of heart attacks, and facial analysis software with consequences on civil liberties. While we underscore the need for integration of AI and HI, we note that AI technology does not have to replace medical specialists or scientists and rather, is in need of such expert HI. Altogether, AI and HI offer synergy for responsible innovation and veritable prospects for improving health care from prevention to diagnosis to therapeutics while unintended consequences of automation emergent from AI and algorithms should be borne in mind on scientific cultures, work force, and society at large.

This research aimed to determine whether there is a relationship between the integration of artificial intelligence and socio-emotional development in university students from southern Peru. A quantitative, non-experimental, correlational, and cross-sectional study was conducted. The sample consisted of 1,172 students of both sexes, selected through non-probabilistic sampling, administered the Artificial Intelligence Integration in Learning Questionnaire and the Socio-Emotional Development Questionnaire, instruments with adequate psychometric properties. The results indicate that the integration of artificial intelligence was moderately adequate, and socio-emotional development was rated moderately. On the other hand, it was determined that Spearman's rho correlation coefficient between both variables was 0.352 (p<0.05). Finally, it was concluded that there is a direct and significant relationship between integrating artificial intelligence and socio-emotional development in university students from southern Peru. This implies that the appropriate use of artificial intelligence tools can enhance socio-emotional skills, fostering a more inclusive and dynamic academic context. Likewise, its implementation could serve as a strategic resource to improve students' social interaction and emotional well-being, contributing to the achievement of comprehensive development in the university setting.

Focus issue: Artificial intelligence in medical physics.

Relevance. The development of artificial intelligence (AI) as a societal foundation has become crucial for leading economies, who view it as a key driver of national competitiveness and security. In an era defined by rapid technological advancement and industrial transformation, nations strive to lead in the international science and technology arena, taking advantage of AI to address challenges across sectors such as agriculture, astronomy, and cybersecurity. AI’s role in enhancing productivity, sustainability, and security highlights its strategic importance, underscoring the urgency for countries to actively pursue AI development to secure a competitive edge in a globalised world. Methodology. The study employs a multi-faceted methodological approach. First, a comprehensive literature review and analysis of AI applications in various sectors, including agriculture, astronomy, and cybersecurity, is conducted to provide context on current advancements and trends. Secondly, a comparative analysis examines the strategic AI policies of leading nations to assess how different countries are positioning AI within their national agendas. Third, case studies of AI implementation in specific sectors, such as precision agriculture and cybersecurity, illustrate the practical impacts and potential benefits of a society-oriented approach to AI. The aim of this study is to analyse the strategic value of fostering an AI-driven society as a means of enhancing national competitiveness and securing leadership in international technological innovation. It aims to explore how AI can be harnessed to support sustainable development, improve sectoral efficiency, and protect against security threats, thus contributing to the overall socio-economic resilience and global standing of a nation. Results. The study reveals that the integration of AI across diverse sectors has led to significant efficiency gains, particularly in resource management, sustainability, and security. AI-driven advancements in agriculture, such as precision farming, contribute to higher productivity and environmental sustainability, while applications in astronomy support large-scale data processing for deep space exploration. In cybersecurity, AI has proven instrumental in identifying and countering cyber threats in real time. These findings confirm that an AI-centric societal model can enhance national resilience, drive economic stability, and bolster a country’s competitive position on the global stage. Conclusion. The emergence and development of the “artificial intelligence society” in the context of the technological transformation of the world is a process in which societies adapt to the profound changes caused by the introduction and development of artificial intelligence (AI) technologies. This process includes several key aspects: economic change, based on the automation of production processes, leading to increased efficiency and productivity; the creation of new markets and business models based on AI capabilities, including the redistribution of jobs and changes in employee skill requirements; social change, which is based on changing the way people interact with each other and with technology; transition to smart cities and communities, where AI helps to manage resources and ensure the comfort of life; impact on education, health and other areas of life through the introduction of personalised AI-based solutions; cultural changes aimed at transforming the values and worldview associated with AI technologies; emergence of new cultural practices and media formats based on AI; development of digital culture and its impact on traditional cultural forms; political and ethical challenges, including defining new regulatory and legal frameworks for AI regulation; ensuring ethical use of AI, avoiding discrimination and ensuring fairness; managing risks related to data security and privacy; technological development, based on the continuous improvement of AI algorithms and models; integration of AI into various sectors of the economy and everyday life’; development of infrastructure to support the large-scale implementation of AI (e.g. 5G networks, data centres); This process reflects the overall technological transformation of the world, where AI is becoming an integral part of economic, social, cultural, and political life. Key words: artificial intelligence, philosophy of society, national competitiveness, strategy.

The article is devoted to the history of the development of Information and Communication Technologies (ICT) and Artificial Intelligence (AI), their current and probable future achievements, and the problems (which have already arisen, but will become even more acute in the future) associated with the development of these technologies and their active introduction in society. The close connection between the development of AI and cognitive science, the penetration of ICT and AI into various fields, in particular the field of health care, is shown. A significant part of the article is devoted to the analysis of the concept of ‘artificial intelligence’, including the definition of generative AI. We analyze recent achievements in the field of Artificial Intelligence, describe the basic models, in particular the Large Linguistic Models (LLM), and forecast the development of AI and the dangers that await us in the coming decades. We identify the forces behind the aspiration to create artificial intelligence, which is increasingly approaching the capabilities of the so-called general/universal AI, and also suggest desirable measures to limit and channel the development of artificial intelligence. The authors emphasize that the threats and dangers of the development of ICT and AI are particularly aggravated by the monopolization of their development by the state, intelligence services, large corporations and those often referred to as globalists. The article forecasts the development of computers, ICT and AI in the coming decades, and also shows the changes in society that will be associated with them. The study consists of two articles. The first, presented below, provides a brief historical overview and characterizes the current situation in the field of ICT and AI, it also analyzes the concepts of artificial intelligence, including generative AI, changes in the understanding of AI related to the emergence of the so-called large language models and related new types of AI programs (ChatGPT). The article discusses the serious problems and dangers associated with the rapid and uncontrolled development of artificial intelligence. The second article, to be published in the next issue of the journal, describes and comments on current assessments of breakthroughs in the field of AI, analyzes various forecasts, and the authors give their own assessments and forecasts of future developments. Particular attention is given to the problems and dangers associated with the rapid and uncontrolled development of AI, the fact that achievements in the field of AI are becoming a powerful means of controlling the population, imposing ideology and choice, influencing the results of elections, and a weapon for undermining security and geopolitical struggle.

In recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered increasing attention from medical experts. This study undertakes a dynamic and longitudinal bibliometric analysis of AI publications within the healthcare sector over the past three decades to investigate the current status and trends of the fusion between medicine and artificial intelligence. Following a search on the Web of Science, researchers retrieved all reviews and original articles concerning artificial intelligence in healthcare published between January 1993 and December 2023. The analysis employed Bibliometrix, Biblioshiny, and Microsoft Excel, incorporating the bibliometrix R package for data mining and analysis, and visualized the observed trends in bibliometrics. A total of 22,950 documents were collected in this study. From 1993 to 2023, there was a discernible upward trajectory in scientific output within bibliometrics. The United States and China emerged as primary contributors to medical artificial intelligence research, with Harvard University leading in publication volume among institutions. Notably, the rapid expansion of emerging topics such as COVID-19 and new drug discovery in recent years is noteworthy. Furthermore, the top five most cited papers in 2023 were all pertinent to the theme of ChatGPT. This study reveals a sustained explosive growth trend in AI technologies within the healthcare sector in recent years, with increasingly profound applications in medicine. Additionally, medical artificial intelligence research is dynamically evolving with the advent of new technologies. Moving forward, concerted efforts to bolster international collaboration and enhance comprehension and utilization of AI technologies are imperative for fostering novel innovations in healthcare.

Artificial Intelligence (AI), due to digitalization, has recently conquered the healthcare disciplines. AI has substantially progressed in healthcare and medical research for preventive, predictive, and personalized care. AI will continue to become the ultimate healthcare-effective tool for serious ailments requiring the early detection of rebuttal. It is a fast-growing automated system based on algorithms positioned to benefit patients, clinicians, researchers, and physicians involved in treatment, prognosis, and preventive care in health. The primary focus of artificial intelligence is technologically expedited solutions to complex challenges. AI's remarkable contribution to machine learning has become a transforming opportunity in medical science. The optimized research, formulation, and development in AI reduce the cost of medical therapy, provide extensive care, improve patient compliance, and promote personalized medicine. The articles were cited from SCI-hub, PUBMED, Scopus, and Google Scholar. AI is assisted with autonomous disease assessing and screening tools that can save time for clinicians and help in the early diagnosis of diabetic retinopathy, cancer detection, and chromosomal disorders to solve complex hurdles. The automated image quality improvement tool makes AI an effective medium for targeting highly complex drug molecules and specific sensors to target organs. Furthermore, the masses have utilized their application in medical devices, pharmaceutical technology, dosage form designing, medical research, and regulatory frameworks to explore the medical era of AI in the healthcare field. However, the integration of AI in medical practice is in the early stages and needs further research to fit an AI model-based approach in clinical settings. AI limitations in health and medical research arise from biases related to gender variation, ethical concerns, complex algorithms, regulatory, cyber security, model evaluation, and problems faced by policymakers. Certain vulnerability factors that can cause health record data breaches and ethical concerns present challenges in healthcare settings due to result failure. Therefore, solutions to overcome these challenges are essential to set the future of AI in clinical research. All such concerns and their solutions must be successfully deployed from research to clinical settings to adopt transformative AI models in medical science. This will help scientists and researchers explore lead molecules and identify newer therapeutic targets. It is crucial to implement measures to control and frame policy guidelines, conduct continuous checks on cybersecurity, solve ethical issues, and consider the possibility of AI adoption in pharmaceutical industries, banking, research areas, hospitals, administration, and clinical practice.

Artificial intelligence is defined as the totality of systems and programs that imitate human intelligence and can eventually surpass this intelligence over time. The rapid development of these technologies has raised various ethical debates such as moral responsibility, privacy, bias, respect for human rights, and social impacts. This study examines the technical infrastructure of artificial intelligence, the differences between weak and strong artificial intelligence, ethical issues, and theological dimensions in detail, providing a comprehensive perspective on the role of artificial intelligence in human life and the problems it brings. The historical development of artificial intelligence has been shaped by the contributions of various disciplines such as mathematical logic, cognitive science, philosophy, and engineering. From the ancient Greek philosophers to the present day, thoughts on artificial intelligence have raised deep philosophical questions such as human nature, consciousness, and responsibility. The algorithms developed by Alan Turing have contributed to the modern shaping of artificial intelligence and have put forward the first models to assess whether machines have human-like intelligence, such as the “Turing Test”. The study first analyzes the technical infrastructure of artificial intelligence in detail and discusses the current limits and potential of the technology through the distinction between weak and strong artificial intelligence. Weak artificial intelligence includes systems designed to perform specific tasks and do not exhibit general intelligence outside of those tasks, while strong artificial intelligence refers to systems with human-like general intelligence and flexible thinking capacity. Most of the widely used artificial intelligence applications today fall into the category of weak artificial intelligence. However, the development of strong artificial intelligence brings various ethical and theological consequences for humanity. The ethical issues of artificial intelligence include fundamental topics such as autonomy, responsibility, transparency, fairness, and privacy. The decision-making processes of autonomous systems raise serious ethical questions at the societal level. Especially autonomous weapons and artificial intelligence-managed justice systems raise concerns in terms of human rights and individual freedoms. In this context, the ethical framework of artificial intelligence has deep impacts on the future of humanity and human-machine interaction, not just limited to technological boundaries. From a theological perspective, the ability of artificial intelligence to imitate the human mind and creative processes raises deep theological issues such as the creativity of God, the place of human beings in the universe, and consciousness. The questions of whether artificial intelligence systems can gain consciousness and whether these conscious systems can have a spiritual status have led to new debates in theology and philosophy. The ethical principles of artificial intelligence are shaped around principles such as transparency, accountability, autonomy, human control, and data management. In conclusion, determining the ethical and theological principles that need to be considered in the development and application of artificial intelligence is critical for the future of humanity. A comprehensive examination of the ethical and theological dimensions of artificial intelligence technologies is necessary to understand and manage the social impacts of this technology. This study emphasizes the necessity of an interdisciplinary approach for the development of artificial intelligence in harmony with social values and for the benefit of humanity. The study provides an important theoretical framework for future research by shedding light on the complex ethical and theological issues arising from the development and widespread use of artificial intelligence.

The integration of artificial intelligence (AI) and machine learning (ML) into regenerative orthopedics heralds a paradigm shift in clinical methodologies and patient management. This review article scrutinizes AI's role in augmenting diagnostic accuracy, refining predictive models, and customizing patient care in orthopedic medicine. Focusing on innovations such as KeyGene and CellNet, we illustrate AI's adeptness in navigating complex genomic datasets, cellular differentiation, and scaffold biodegradation, which are critical components of tissue engineering. Despite its transformative potential, AI's clinical adoption remains in its infancy, contending with challenges in validation, ethical oversight, and model training for clinical relevance. This review posits AI as a vital complement to human intelligence (HI), advocating for an interdisciplinary approach that merges AI's computational prowess with medical expertise to fulfill precision medicine's promise. By analyzing historical and contemporary developments in AI, from the foundational theories of McCullough and Pitts to sophisticated neural networks, the paper emphasizes the need for a synergistic alliance between AI and HI. This collaboration is imperative for improving surgical outcomes, streamlining therapeutic modalities, and enhancing the quality of patient care. Our article calls for robust interdisciplinary strategies to overcome current obstacles and harness AI's full potential in revolutionizing patient outcomes, thereby significantly contributing to the advancement of regenerative orthopedics and the broader field of scientific research.

The innovative development of medicine is synchronized with the innovative application of technology. Also, artificial intelligence technology brings new breakthroughs for medical research in the era of artificial intelligence. In particular, artificial intelligence technology has achieved conspicuous application expectations in medical image, realized the integration of intelligent technology and medical image research, and provided assistance for tumor diagnosis and cardiovascular disease diagnosis. As a computer technology operating in human thinking mode, artificial intelligence technology realized the imitation of human brain thinking process and overcame the subjective bias of human brain thinking, which is of great application value. The integration of artificial intelligence technology and medical image is an inevitable trend and the dawn of medical progress. In the new era, it is valuable to increase the research on the integration of artificial intelligence technology and medicine in order to realize the new development of medicine supported by artificial intelligence technology. In this context, this work mainly discussed the integration and development of artificial intelligence technology and medical image and analyzed the application of artificial intelligence technology in medical image on the basis of clarifying the current situation of medical application of artificial intelligence technology.

Artificial intelligence has slowly become the focus of research in various countries, and the application of artificial intelligence has become more and more extensive, and it can be seen in more and more industries. However, the application of artificial intelligence technology to the sports industry is still an attempt with unpredictable results, but it will be a bold attempt. In addition, in the process of the integration and development of artificial intelligence and the sports industry, there must be some problems. This requires researchers and staff to have enough patience to solve these problems, and through joint efforts to continuously improve, make artificial intelligence and sports the integrated development of the industry is more stable. This paper adopts a combination of empirical analysis and theoretical analysis, systematically researches the current status of the development of the sports industry with artificial intelligence, and analyzes the development trend of this new type of sports industry. The results of the experiment show that the market size of China’s artificial intelligence sports education and the growth rate of the number of users have both remained above 20%, which has doubled in just four years, showing the rapid development of it. It proves from the side that the unique environmental advantages and sufficient talent advantages of the artificial intelligence sports industry have laid a strong human resource foundation for the sports industry in the central plains urban agglomeration; the artificial intelligence sports industry has a wealth of traditional characteristic sports industry projects, and is the development of the artificial intelligence sports industry provides a rich resource base for the sports industry.