Smart Cities and Medical Tourism: Leveraging AI in Urban Marketing to Enhance Patient Experience

Purpose This study aims to investigate ethical consideration into the data quality management and biases for fairness in artificial intelligence (AI) algorithms. It looks at how biases in AI systems could make it difficult to maintain data quality control in medical travel and tourism. Design/methodology/approach The systematic review of the literature from January 2019 to March 2025 (72 out of 925 articles) considers a variety of keyword combinations used for data quality control in AI systems. The process of systematic literature review aids in identifying studies on data quality management for medical tourism and travel. Findings The results of the study show that data quality visibility should be increased, data rectification should be done consistently and data momentum should be managed. It indicates that audience behavior in medical travel and tourism is significantly impacted by AI-powered digital branding and marketing. Research limitations/implications The research is limited to the single source of methodology, and it is limited in terms of articles collected from Jan 2019 to March 2025. It can be extended to the last decade for more insights and issues in AI use for medical travel and tourism. Practical implications Practical applications include efficient patient processing for international medical travel and tourism, as well as automated AI machine learning. Future research investigations should consistently segment data evaluation to overcome the limited regulatory compliance of data quality management. Social implications Patients (medical tourism) are primary elements in healthy social settings that can be facilitated through AI’s efficient use and maintaining the quality of the data management. Originality/value This study aims to address the main ethical concerns about the quality of AI data, data use monitoring and ethical support for data decisions and implementations inside the AI framework. The usage of digital branding, mobile app development, digital audience behavior, digital marketing principles and artificial intelligence in marketing are some of the important concepts used to accomplish the research goals.

Improvements in the artificial intelligence (AI) health system have been effective in reducing the risks associated with transgender medical tourism and travel. The ability to track medical travel from the place of origin to the final treatment destination is dependent on the development of AI. This project aims to improve the AI health system to promote travel and medical tourism, utilizing quantitative research methodologies, including survey-based research and partial least squares structural equation modeling. The participants included 381 people from medical professionals, tourism experts, transgenders, and technology enthusiasts interested in AI and health. The findings show that the AI health system has significantly improved medical travel and tourism; key factors such as medical tourism, AI systems, medical travel and risk factors, attitude, behavioral intention, and medical destination image have all contributed to better healthcare experiences for transgender individuals. Specialized care should be provided to transgender individuals traveling for surgeries and medical treatments, emphasizing their unique needs. Subsequent investigations might focus on the broader function of AI, particularly in terms of ensuring the dignity and respect of the tourism site. This study proposes further integration of AI into healthcare systems to maximize the benefits of safe medical travel and secure tourist locations.

Rapid urbanization and low residential resources in cities are serious issues that are making city life difficult day by day. The development of smart cities is becoming a need of the present era due to the swift increase in population and environmental issues globally. Smart cities are being introduced in different regions of the world with the incorporation of latest technologies. The incorporation of Artificial Intelligence (AI) is one of the tools that can be used in smart building and cities. AI technologies are transforming public safety, trash management, healthcare, traffic control, and resource management, making cities more sustainable, effective, and responsive to their citizens' demands. There are still lack of awareness in some areas of the world on the efficacy of smart building and construction that is impacting negatively on the economy and growth of those countries.; such as Pakistan is one of those countries that is facing serious challenges due to increased population, urban migration, and poor management of natural resources. The need of planning smart strategies for smart building is very crucial to manage population and housing issues. Smart buildings and cities provide unique and convenient facilities to its residents so that they can contribute positively towards the economy of country. This paper focuses at important areas where AI has the most effects in order to investigate how integrating AI improves quality of life in smart cities. The aim is to highlight artificial intelligence's contribution to improving urban operations, streamlining resource management, and advancing sustainability. Additionally, potential concerns about privacy, data security, and fair access will be discussed. In order to show how AI-driven innovations like predictive analytics, machine learning, and IoT-enabled systems are changing the urban environment, the study synthesizes existing research and real-world examples. The evaluation also covers how AI promotes smart government, tailored urban services, and citizen involvement. The conclusion emphasizes that although AI has great potential to improve the quality of life in smart cities, implementation of the technology must be done in a balanced way to prioritize inclusive policies and ethical concerns for the general welfare of residents.

General Background – Health tourism is a rapidly expanding industry driven by innovation and digital transformation, offering high-quality and cost-effective healthcare solutions globally. Specific Background – Despite its growth, there is limited research on the integration of digital technologies such as telemedicine, artificial intelligence, and blockchain in enhancing patient experience and operational efficiency. Knowledge Gap – Previous studies have primarily focused on infrastructure, patient motivation, and service quality, leaving a gap in understanding the role of digital transformation in health tourism. Aims – This study aims to analyze trends in health tourism innovation, mapping technological advancements, policy adaptations, and business model transformations using bibliometric analysis. Results – Findings indicate that digital health solutions, particularly telemedicine and Electronic Health Records (EHR), significantly enhance accessibility and service quality. Future research should focus on data-driven technologies and sustainable business models. Novelty – This study contributes by systematically mapping digital innovations in health tourism through bibliometric analysis, offering a comprehensive perspective on the industry's evolution. Implications – The findings provide strategic insights for policymakers and industry stakeholders, emphasizing the importance of standardized business process modeling to enhance service efficiency and competitiveness in global health tourism markets. Highlights: Digital Transformation in Health Tourism – The integration of telemedicine, AI, and blockchain enhances patient experience, accessibility, and service efficiency. Bridging the Knowledge Gap – This study fills a research gap by systematically mapping digital innovations in health tourism through bibliometric analysis. Strategic Implications – Findings provide actionable insights for policymakers and industry leaders to standardize business processes and improve global competitiveness. Keywords: Health Tourism, Development, Innovation

The rapid advancement of technology has strengthened the relationship between health tourism and artificial intelligence (AI), making this field increasingly important from both academic and practical perspectives. In the context of health tourism, AI-supported technologies play a critical role in developing marketing strategies, enhancing patient experience and service quality, and improving operational efficiency in healthcare services. This study aims to examine academic research on AI-supported health tourism through a bibliometric analysis. Within the scope of the study, publications indexed in the Web of Science (WoS) database were analyzed in terms of annual scientific production, leading authors and countries, collaboration networks, influential journals, frequently used keywords, and emerging research trends. The findings indicate that academic publications on AI-supported health tourism have been indexed in the WoS database since 1990 and have shown a marked increase, particularly after 2019. The highest number of publications was reached in 2024, with a total of 50 studies published. In total, 207 studies were published across 177 different sources, with an average annual growth rate of 5.72%. A total of 1,037 researchers contributed to these publications, with an average of 5.22 authors per study, indicating a strong collaborative research structure. Sensors emerged as the most productive journal, while Artificial Intelligence in Medicine was among the most highly cited sources. In terms of geographical distribution, researchers from the United States produced the highest number of publications, followed by China and Italy. Keyword analysis revealed that the most frequently used terms included artificial intelligence, system, model, internet, diagnosis, and wellness. The significant increase in AI-related studies after 2019 highlights the growing prominence of artificial intelligence as a central research theme within health tourism. Overall, the findings suggest that AI-supported health tourism will continue to attract increasing academic attention and will play a pivotal role in shaping the future of the sector.

Purpose – The purpose of this paper is to propose a novel theoretical framework that explores the integration of Artificial Intelligence (AI) into the medical tourism sector, with the aim of enhancing healthcare accessibility, efficiency, and patient satisfaction. The framework is designed to address the challenges faced by medical tourism destinations, such as high treatment costs, accessibility issues, and operational inefficiencies. Design/methodology/approach – This study employs a conceptual methodology, combining a comprehensive review of current AI applications in healthcare and the development of a new framework tailored to medical tourism. The framework integrates AI-driven predictive analytics, virtual health assistants, and personalized treatment algorithms. Furthermore, a mathematical model is proposed to substantiate the framework, demonstrating its impact on key performance indicators (KPIs) in medical tourism. Findings – The paper finds that AI can significantly improve operational efficiency, reduce treatment costs, enhance patient satisfaction, and increase the competitiveness of medical tourism destinations. The proposed framework shows how AI can address critical challenges such as language barriers, healthcare quality discrepancies, and patient navigation difficulties. Practical implications – The findings suggest that healthcare providers and policymakers in medical tourism destinations can leverage AI technologies to improve service delivery, attract more international patients, and foster economic growth in the sector. The study provides actionable recommendations for the adoption of AI in medical tourism, which could lead to a more efficient, affordable, and patient-friendly healthcare experience. Originality/value – This paper offers a novel theoretical framework that integrates AI into the medical tourism industry, which has not been sufficiently explored in existing literature. The proposed model contributes to a better understanding of how AI can enhance the quality, accessibility, and efficiency of healthcare services for international patients.

The proposed chapter delves into the transformative repercussions of Robotics and Artificial Intelligence (AI) on the burgeoning Indian Medical Travel and Tourism Sector. As India emerges as a global hub for medical tourism, the integration of innovative technologies promises to reshape patient experiences and healthcare delivery. The chapter meticulously investigates the expansion of the medical travel sector in India, the role of AI in healthcare, the impact of robotics, and the intersection of these technologies in the context of medical tourism. It not only highlights the positive outcomes and success stories but also addresses the challenges and ethical concerns related to healthcare robots and artificial intelligence. Furthermore, the chapter provides a forecast for the future of these technologies in India's wellness sector, offering recommendations for stakeholders to navigate the evolving landscape successfully.

While many studies have addressed health communication and physician-patient interactions, knowledge about intercultural communication in medical tourism is limited. Our empirical study, therefore, investigates aspects related to patients' cultural beliefs regarding the quality of healthcare and the way this shapes their expectations and experiences in an intercultural medical interview setting at a Joint Commission International (JCI) accredited host country hospital in India. The theoretical foundation is the Communication Accommodation Theory. A quantitative design was used in this study using the convenience sampling method. Data were collected from 300 medical tourism (MT) patients immediately after their face-to-face medical interview at the hospital. The non-Western cultures displayed higher intercultural communication (ICC) expectations from the host country doctors than the Western patients, possibly on account of cultural similarity with and proximity to the host country. ICC beliefs of MT patients supported by convergent communication accommodation by the doctors led to the perception of better ICC experience in clinical consultations with the potential to improve word-of-mouth promotion, patient satisfaction and revisit intentions; patients' expectations mediated the relationship. Consultation time in minutes controlled the relationship between patient ICC beliefs, expectations and experience in the medical consultations. The proposed model was undifferentiated for age, gender and geography of the MT patient as well as wait time (in minutes). While culture has been recognised as a significant factor in shaping the growth in medical tourism, research is scant on cultural and religious communication accommodation practices of host country doctors and medical staff and its effects on patient experience. Most studies on culture and MT have either evaluated the role of culture on the destination choice of international patients (cultural affinity or cultural familiarity) or have analysed the effect of distance between the host and the guest country as critical determinants of the choice of MT country. This study is probably the first to assess the quality of ICC beliefs, expectations and effects on MT patients' experiences. It is also the pioneering study to relate the context of MT with the well-regarded Communication Accommodation Theory, especially the manner in which convergent and divergent accommodation occurred between MT patients and MT service providers in the host country.

AI's integration and adoption in the sector have evolved to be a game-changer through operational revolutionisation regarding accessibility to advanced diagnosis and treatments, reduced waiting times, and cost savings. This chapter explores the strategic efficacy of AI in the context of medical tourism. Using the term “strategic efficacy,” the authors encompass the concept of efficiency and effectiveness of AI in achieving a strategic outcome in medical tourism. The authors' purviews are that is important to ensure that an AI strategy in medical tourism not only looks good on paper but also continues to produce high success for the global practice. In this chapter, the authors discuss AI's emergence in the medical tourism industry, the strategic efficacy of AI in medical tourism, the categories of AI-system devices used in medical tourism, and the AI-system devices. Also discussed are AI systems applications to some major diseases in medical tourism.

Objective: Medical tourism presents unique opportunities for delivering patient-centered healthcare, yet the role of artificial intelligence (AI) in enhancing management processes within the patient journey remains underexplored. This study aims to investigate AI’s potential to optimize patient experience and operational efficiency in medical tourism by proposing a comprehensive conceptual framework. Methods: A structured literature review was conducted, analyzing a total of 100 publications (95 peer-reviewed articles and 5 industry reports) published between 2007 and 2023. Thematic analysis was employed to synthesize findings and develop the AI-Enhanced Medical Tourism Patient Journey Model (AI-MTPJM), integrating AI applications across key stages of the patient journey. Results: The AI-MTPJM framework outlines five main stages of the medical tourism patient journey: (1) Information Search, (2) Planning and Reservation, (3) Travel and Treatment, (4) Post-treatment Follow-up, and (5) Feedback and Loyalty. Various AI technologies such as virtual assistants, predictive analytics, real-time monitoring, telemedicine, and sentiment analysis are mapped to these stages. These tools contribute to personalized services, improved operational workflows, and enhanced patient satisfaction in international medical tourism destinations. Conclusion: The AI-MTPJM serves as a strategic bridge between patient-centered service design and data-driven healthcare management. While it holds significant potential for strengthening the competitiveness of medical tourism providers, challenges such as data privacy, cost, and infrastructure requirements must be carefully managed. This framework offers practical insights for stakeholders and lays the groundwork for future empirical research on AI integration in medical tourism management.

The burgeoning evolution of smart cities, characterized by the integration of the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML), heralds a transformative era in urban management and citizen engagement. These technological advancements promise enhanced efficiency in city operations, improved public services, and a sustainable urban environment. However, the complexity and interconnectedness inherent in these systems introduce significant cybersecurity challenges, necessitating innovative approaches to safeguard the digital infrastructure of smart cities. This paper aims to explore the cybersecurity landscape of smart cities from the perspective of integrating IoT, AI, and ML for the creation of digital twins, offering a comprehensive analysis of the opportunities and threats within this domain. Smart cities leverage IoT to connect various components of the urban infrastructure, including transportation systems, utilities, and public services, creating an integrated network of devices that communicate and share data. The incorporation of AI and ML into this framework facilitates intelligent decision-making, enabling the automation of services and the optimization of resources. This synergy enhances the quality of life for residents, promotes economic development, and supports sustainable environmental practices. However, the dependence on digital technologies also exposes smart cities to a range of cybersecurity risks, from data breaches and privacy violations to the disruption of critical infrastructure. The integration of IoT, AI, and ML in smart cities, while offering unprecedented opportunities for urban innovation, also amplifies the complexity of the cybersecurity landscape. IoT devices, often designed with minimal security features, become potential entry points for cyber attacks. The vast amount of data generated and processed by these devices, if compromised, could lead to significant privacy and security breaches. AI and ML models, for their part, are susceptible to manipulation and bias, which can undermine the integrity of decision-making processes. The interconnectivity of systems means that a breach in one sector could have cascading effects throughout the city's infrastructure. Against this backdrop, the paper investigates the role of digital twins in mitigating cybersecurity risks in smart cities. Digital twins, digital replicas of physical entities or systems, offer a powerful tool for simulating and analyzing smart city operations, including cybersecurity scenarios. By mirroring the city's infrastructure in a virtual environment, digital twins allow for the identification of vulnerabilities, the simulation of cyber attacks, and the evaluation of potential impacts. This proactive approach to cybersecurity enables city administrators to anticipate threats and implement protective measures before real-world systems are compromised. The research questions guiding this inquiry include: How can the integration of IoT, AI, and ML enhance the resilience of smart cities against cyber threats? What are the specific cybersecurity challenges presented by these technologies, and how can they be addressed? And, most crucially, what role can digital twins play in fortifying the cybersecurity defenses of smart cities? To address these questions, the paper begins with a review of the current state of smart city technology, focusing on the integration of IoT, AI, and ML. It then delves into the cybersecurity challenges unique to this technological landscape, drawing on recent examples of cyber incidents in smart cities. The analysis highlights the vulnerabilities introduced by the widespread use of IoT devices and the complexities of securing AI and ML systems. Following this, the discussion turns to the potential of digital twins as a cybersecurity tool, examining how they can be employed to detect vulnerabilities, simulate attacks, and plan responses. The paper argues that while the integration of IoT, AI, and ML in smart cities presents significant cybersecurity challenges, it also offers opportunities for innovative solutions. Digital twins emerge as a promising approach to enhancing the cybersecurity posture of smart cities, enabling a dynamic and proactive defense mechanism. By facilitating the simulation of cyber threats in a controlled environment, digital twins allow city administrators to identify weaknesses, test the efficacy of protective measures, and develop more resilient urban infrastructures. In conclusion, the integration of IoT, AI, and ML in smart cities represents a double-edged sword, offering both remarkable opportunities for urban innovation and formidable cybersecurity challenges. This paper underscores the critical importance of adopting a cybersecurity perspective in the development and management of smart cities, highlighting the potential of digital twins as a strategic tool in mitigating these risks. As smart cities continue to evolve, embracing these technologies in a secure and responsible manner will be paramount in realizing their full potential while safeguarding the digital and physical well-being of urban populations.

Introduction: Health tourism is one of the rapidly growing industries worldwide, driven by the increasing demand for high-quality medical services at lower costs. In this context, artificial intelligence (AI), as an emerging technology, plays a crucial role in improving service quality, enhancing efficiency, and reducing costs associated with this field. Objective: The aim of this research is to identify opportunities, challenges, and future trends in the application of AI in health tourism, providing a comprehensive perspective for policymakers, healthcare service providers, and professionals in this sector. Methodology: This study is a systematic review conducted in accordance with PRISMA guidelines. A literature search was performed in reputable databases, including PubMed, Scopus, Web of Science, and Google Scholar, using keywords related to "artificial intelligence" and "health tourism." Studies published between 2010-2025 were reviewed. Results: The findings of this study indicate that artificial intelligence has a significant impact on the development of health tourism. The most important applications of AI in this field include optimizing appointment scheduling and booking systems, intelligent diagnosis and treatment, personalized medical services, efficient management of international patients, and enhancing the patient experience. Additionally, the use of AI can lead to cost reduction, increased diagnostic accuracy, and improved quality of healthcare services for health tourists. Conclusion: Artificial intelligence plays a significant role in improving and developing health tourism, leading to increased efficiency, cost reduction, and enhanced service quality. However, challenges such as implementation costs and ethical issues need to be addressed. The development of supportive policies and technological infrastructure can help effectively leverage this technology in health tourism.

INTRODUCTION: Internet of Things (IoT) has been taking wide place in our daily lives. Among different solution ways in terms of IoT, wearables take a remarkable role because of their compact structures and the mobility. By using wearables, it is very easy to sense a person’s movements and gather characteristic data, which may be processed for desired outcomes if intelligent inferencing. As associated with this, wearables can be effectively used for health tourism operations. As wearables already proved their capabilities for healthcare-oriented applications, the perspective may be directed to health tourism purposes. In this way, positive contributions may be done in the context of not only patients’ well-being but also other actors such as health staff and tourism agencies.OBJECTIVES: Objective of this paper is to evaluate the potential of wearables in health tourism applications, provide a model suggestion, and evaluate it in the view of different actors enrolling in health tourism ecosystems. Within this objective, research targets were directed to the usage ways of wearables in health tourism, ensuring model structures as meeting with the digital transformation advantages, and gather some findings thanks to feedback by patients, health staff, and agencies.METHODS: The research firstly included some views on what is health tourism, how the IoT, mobile solutions as well as wearables may be included in the ecosystem. Following to that, the research ensured a model suggestion considering wearables and their connections to health tourism actors. Finally, the potentials of wearables and the model suggestion was evaluated by gathering feedback from potential / active health tourists, health staff, and agency staff. RESULTS: The research revealed that the recent advancements in wearables and the role of digital transformation affects health tourism. In this context, there is a great potential to track and manage states of all actors in a health tourism eco system. Thanks to data processing and digital systems, it is effective to rise fast and practical software applications for health tourism. In detail, this may be structured in a model where typical IoT and wearable interactions can be connected to sensors, databases, and the related users. According to the surveys done with potential / active health tourists, health staff, and agency staff, such a model has great effect to advance the health tourism.CONCLUSION: The research study shows positive perspectives for both present and future potentials of wearable and health tourism relation. It is remarkable that rapid advancements in IoT can trigger health tourism and the future of health tourism may be established over advanced applications including data and user-oriented relations.

Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review

Background and Aims: The primary objective of this study is to evaluate the performance of the ChatGPT as an expert in the field of medical tourism. Another objective of this study is to assess its evaluations regarding the current state and future prospects of medical tourism in Turkey from an artificial intelligence perspective. Methods: Within the scope of the study's objectives, questions were created for ChatGPT regarding the current state and future prospects of medical tourism in Turkey. First, the draft questions were prepared by the authors of this article using the literature. All questions were evaluated by experts through online interviews. Totally 8 experts have been evaluated the questionnaires. These experts consisted of two tourism professors who had research on medical tourism, three major medical tourism hospital managers, one reconstructive aesthetician clinic owner, and the Turkish Healthcare Travel Council Founding Chairman. The second step of the research questionnaire was applied to the ChatGPT Model 4, which was trained as a medical tourism expert. than test the answers of the AI used the tools “Completeness of content, Lack of false information in the content, Evidence supporting the content, Appropriateness of the content, and Relevance,” referred as CLEAR. All answers were evaluated by 41 experts who had articles and research on medical tourism in Turkey. To explain the methodology appropriately, reporting was conducted using the METRICS checklist, which was prepared for artificial intelligence studies. Results: TThe general answers of ChatGPT 4-o were accurate, informative, and helpful, providing a good overview of medical tourism in Turkey. However, the responses lacked detail, did not provide evidence-based information, and did not always address the nuances and cultural/social impacts of medical tourism. ChatGPT 4-o views the future of Turkey’s medical tourism as shiny and will force the lead in general. Conclusions: This study is important for revealing data on the current and future state of medical tourism through artificial intelligence. However, only a few studies have been conducted on artificial intelligence and medical tourism. To the best of our knowledge, there is no existing literature that systematically evaluates the ChatGPT responses of medical tourism experts. In this regard, it is believed that the study will benefit both academics and practitioners.