Inteligencia artificial en la sostenibilidad del turismo de salud: Una revisión sistemática
Palabras clave:
Inteligencia artificial, metodología PRISMA, sostenibilidad, turismo de salud, turismo médicoResumen
Introducción: La inteligencia artificial emerge como una herramienta transformadora para impulsar la sostenibilidad en el turismo de salud, un sector en rápido crecimiento, al optimizar la gestión de recursos y personalizar experiencias que respetan el bienestar tanto del visitante como del entorno local.
Objetivo: Identificar, analizar y sintetizar el papel de la Inteligencia artificial en la sostenibilidad del turismo de salud a través de una revisión sistemática de la literatura.
Material y Métodos: Se realizó un artículo de revisión sistemática basada en metodología PRISMA. Se analizaron 33 estudios de las bases de datos Scopus y Web of Science, con publicaciones comprendidas entre 2020 y 2025. Se estudiaron las variables: tecnologías de inteligencia artificial aplicaciones orientadas a la sostenibilidad, destinos y actividades asociadas al turismo de salud, implicaciones económicas y sociales, oportunidades y desafíos del uso de la inteligencia artificial.
Resultados: El aprendizaje supervisado, aprendizaje no supervisado, aprendizaje por refuerzo, aprendizaje profundo, redes neuronales, modelos híbridos y modelos de lenguaje, así como inteligencia artificial simbólica, son tecnologías ampliamente utilizadas en el turismo de salud. Estas tecnologías se aplican en seis áreas funcionales: sistemas de recomendación y soporte a la toma de decisiones, predicción de la demanda y planificación estratégicas, segmentación y personalización de servicios, automatización de procesos operativos, comunicación multilingüe y accesibilidad y diagnóstico y monitoreo clínico remoto.
Conclusiones: La inteligencia artificial contribuye activamente a la sostenibilidad del turismo de salud mediante la optimización de recursos, la mejora de la experiencia del paciente y el fortalecimiento de la competitividad de los destinos.
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1. Dalkıran GB. Health Tourism Components and Intermediary Institutions as Supplier Businesses in the Context of Health 4.0. En: İyigün I, Görçün ÖF, Eds. Health 4.0 and Medical Supply Chain. pp. 147-162 [Internet]. Philadelphia: Springer Nature; 2023. Disponible en: https://doi.org/10.1007/978-981-99-1818-8_12
2. Dar H, Kashyap K. Smart Healthcare System (SHS): Medical Tourism Delivering, Consumption, and Elevating Tool in the Ages of Smart Technologies. Tourism Planning & Development [Internet]. 2023;20(3):397-415. Disponible en: https://doi.org/10.1080/21568316.2022.2109206
3. Ahani A, Nilashi M, Zogaan WA, Samad S, Aljehane NO, Alhargan A, et al. Evaluating medical travelers’ satisfaction through online review analysis. Journal of Hospitality and Tourism Management [Internet]. 2021;48:519-37. Disponible en: https://doi.org/10.1016/j.jhtm.2021.08.005
4. Siddik AB, Forid S, Yong L, Du AM, Goodell JW. Artificial intelligence as a catalyst for sustainable tourism growth and economic cycles. Technological Forecasting and Social Change [Internet]. 2025;210:123875. Disponible en: https://doi.org/10.1016/j.techfore.2024.123875
5. Sharma S, Chauhan Y, Tyagi R. Artificial Intelligence based Applications in Medical Tourism. En: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) [Internet]. Berlin: ResearchGate GmbH; 2023. Pp.1-6. Disponible en: https://doi.org/10.1109/ICCCNT56998.2023.10308020
6. Florido-Benítez L, del Alcázar Martínez B. How Artificial Intelligence (AI) Is Powering New Tourism Marketing and the Future Agenda for Smart Tourist Destinations. Electronics [Internet]. 2024;13(21). Disponible en: https://doi.org/10.3390/electronics13214151
7. García-Madurga M-Á, Grilló-Méndez A-J. Artificial Intelligence in the Tourism Industry: An Overview of Reviews. Administrative Sciences [Internet]. 2023;13(8). Disponible en: https://doi.org/10.3390/admsci13080172
8. Sousa AE, Cardoso P, Dias F. The Use of Artificial Intelligence Systems in Tourism and Hospitality: The Tourists’ Perspective. Administrative Sciences [Internet]. 2024; 14(8). Disponible en: https://doi.org/10.3390/admsci14080165
9. Dai H, Lee S-N, Chong KM. An Artificial Intelligence Prediction Approach for Behavioral Intentions of Health Tourism: A Protection Motivation Theory-based Perspective. Applied Mathematics and Nonlinear Sciences [Internet]. 2024;9(1). Disponible en: https://doi.org/10.2478/amns-2024-2747
10. Rady A, Wahab HA. The Role of Artificial Intelligence to Enhance Health Tourism Applications in Egyptian Tourist Destinations. Minia Journal of Tourism and Hospitality Research MJTHR [Internet]. 2024;17(2):44-62. Disponible en: https://doi.org/10.21608/mjthr.2024.281385.1150
11. Page MJ, McKenzie J, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ [Internet]. 2021;372(71). Disponible en: https://doi.org/10.1136/bmj.n71
12. Pranckutė R. Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World. Publications [Internet]. 2021; 9(1). Disponible en: https://doi.org/10.3390/publications9010012
13. Mishra D, Panda R. How Delightful is Indian Wellness Tourism? A Netnographic Study. Advances in Hospitality and Tourism Research (AHTR) [Internet]. 2021; 9(1). Disponible en: https://doi.org/10.30519/ahtr.784232
14. Nagar R, Singh Y, Malik M, Dalal S. FdAI: Demand Forecast Model for Medical Tourism in India. SN Computer Science [Internet]. 2024;5(4):431. Disponible en: https://doi.org/10.1007/s42979-024-02724-5
15. Nilashi M, Samad S, Ahani A, Ahmadi H, Alsolami E, Mahmoud M, et al. Travellers decision making through preferences learning: A case on Malaysian spa hotels in TripAdvisor. Computers & Industrial Engineering [Internet]. 2021;158: 107348. Disponible en: https://doi.org/10.1016/j.cie.2021.107348
16. Talayeh S, Firouzi F, Bahman F. Presenting a Model for Predicting Demand in the Supply Chain of Medical Tourism. Payavard Salamat [Internet]. 2021;17(5):386-95. Disponible en: http://payavard.tums.ac.ir/article-1-7292-en.html
17. Torkzadeh L, Jalilian H, Zolfagharian M, Torkzadeh H, Bakhshi M, Khodayari-Zarnaq R. Market segmentation in the health tourism industry: A systematic review of approach and criteria. Journal of Policy Research in Tourism, Leisure and Events [Internet]. 2024;16(1):69-88. Disponible en: https://doi.org/10.1080/19407963.2021.1988622
18. Yıldız M, Aydin MA, Gökçay G, Kizilarslan V, Yaman U. The effect of intercultural sensitivity and ethnocentrism on health tourism awareness level in nurses: Analysis with machine learning approach. Archives of Psychiatric Nursing [Internet]. 2023; 46: 40-50. Disponible en: https://doi.org/10.1016/j.apnu.2023.07.002
19. Nagar R, Singh Y, Jaglan V, Meenakshi A. A Review on Machine Learning Applications in Medical Tourism. En: 2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT) [Internet]. Berlin: ResearchGate GmbH; 2021.pp. 208-15. Disponible en: https://doi.org/10.1109/CCICT53244.2021.00048
20. Pinos-Navarrete A, Abarca-Álvarez FJ, Maroto-Martos JC. Perceptions and Profiles of Young People Regarding Spa Tourism: A Comparative Study of Students from Granada and Aachen Universities. International Journal of Environmental Research and Public Health [Internet]. 2022;19(5):2580. Disponible en: https://doi.org/10.3390/ijerph19052580
21. Ramos CM, Ashqar RI. Machine Learning in Health and Wellness Tourism. HCI International 2023 – Late Breaking Papers: 25th International Conference on Human-Computer Interaction, HCII 2023, Copenhagen, Denmark, July 23–28, 2023, Proceedings, Part VII [Internet]. Berlin: ResearchGate GmbH; 2023. pp. 502-18. Disponible en: https://doi.org/10.1007/978-3-031-48060-7_39
22. Laosen N, Laosen K, Ardharn J. Intent Classification from Online Forums for Phuket Medical Tourism. 2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) [Internet]. 2023;1-4. Disponible en: https://doi.org/10.1109/ECTI-CON58255.2023.10153301
23. Pereira TC, Costa E, Borges I, Silva FM, Pinto AS, Vázquez-Justo E. Health Tourism Monitor System Model. En: de Carvalho JV, Liberato P, Peña A, Eds. Advances in Tourism, Technology and Systems [Internet]. Philadelphia: Springer Nature; 2022. pp. 605-13. Disponible en: https://doi.org/10.1007/978-981-16-9701-2_50
24. Jatmika S, Patmanthara S, Wibawa Aji P, Kurniawan F. The model of local wisdom for smart wellness tourism with optimization multilayer perceptron. Journal of Theoretical and Applied Information Technology. 2024;102(2).
25. Subasinghe M, Magalage D, Amadoru N, Amarathunga L, Bhanupriya N, Wijekoon JL. Effectiveness of artificial intelligence, decentralized and distributed systems for prediction and secure channelling for Medical Tourism. 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) [Internet]. Berlin: ResearchGate GmbH; 2020. Pp. 0314-0319. Disponible en: https://doi.org/10.1109/IEMCON51383.2020.9284898
26. Chen P. Strategy of Artificial Intelligence Assisted Health Tourism in the Perspective of Global Region Based on Markov Chain Model. 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC) [Internet]. Berlin: ResearchGate GmbH; 2020. pp.391-4. Disponible en: https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00073
27. Lin M. Evaluation model of South China Sea tourism venture capital based on improved GA neural network under the background of health tourism industry development. Environment, Development and Sustainability [Internet]. 2025; 27(2): 4185-201. Disponible en: https://doi.org/10.1007/s10668-023-04069-0
28. Bo KJJ, Tongtep N, Kamonmarttayakul K. Customer Insight Analysis with Sentiments and Topic Modeling from Wellness Centers in Phuket. 2024 28th International Computer Science and Engineering Conference (ICSEC) [Internet]. Berlin: ResearchGate GmbH; 2024. Pp. 1-6. Disponible en: https://doi.org/10.1109/ICSEC62781.2024.10770722
29. Halkiopoulos C, Dimou E, Kompothrekas A, Telonis G, Boutsinas B. The E-Tour Facilitator Platform Supporting an Innovative Health Tourism Marketing Strategy. En: Katsoni V, van Zyl C, Eds. Culture and Tourism in a Smart, Globalized, and Sustainable World [Internet]. Philadelphia: Springer International Publishing; 2021. pp. 609-23. Disponible en: https://doi.org/10.1007/978-3-030-72469-6_39
30. Akpur A, Enes K. Evaluating ChatGPT’s Role in Assessing Turkey’s Medical Tourism Trends. Jordan Medical Journal [Internet]. 2024; 58(4). Disponible en: https://doi.org/10.35516/jmj.v58i4.3142
31. Sakipov N, Vikhnin O. The Modern Symbolic Artificial Intelligence and Its Use in Medical Tourism. 2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) [Internet]. Berlin: ResearchGate GmbH; 2021. Pp. 1-6. Disponible en: https://doi.org/10.1109/AICT52784.2021.9620321
32. Kundury KK, Shetty SP, Kuldeep GB. A Bird’s-Eye-View on Technological Advancements in Medical Tourism. En: Chaudhary B, Bhatia D, Patel M, Singh S, Sharma S, Eds. Medical Tourism in Developing Countries: A contemporary approach [Internet]. Philadelphia: Springer Nature; 2024. pp. 175-98. Disponible en: https://doi.org/10.1007/978-981-99-8909-6_12
33. Rajković I, Baričević D, Šimunić M. Overview of different IT solutions for reducing no-shows and unexplained patient cancellations in health tourism [Internet]. Berlin: ResearchGate GmbH; 2024. Pp.167-75. Disponible en: https://doi.org/10.20867/thi.27.21
34. Reshadi MS, Chehragh AM. A review of medical tourism entrepreneurship and marketing at regional and global levels and a quick glance into the applications of artificial intelligence in medical tourism. AI Society [Internet]. Berlin: ResearchGate GmbH; 2025. Disponible en: https://doi.org/10.1007/s00146-024-02178-6
35. Tripathi RP, Shalki P. Harnessing the Potential of AI and ML in Medical Tourism: Challenges, Opportunities, and Ethical Implications. 2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS), [Internet]. Berlin: ResearchGate GmbH; 2023. Pp. 1068-72. Disponible en: https://doi.org/10.1109/ICTACS59847.2023.10390358
36. Dávila-Aragón G, Arrioja-Castrejón E. Medical Tourism in Mexico. Analysis of the Economic and Technological Model in the COVID-19 Pandemic Era. En: Dávila-Aragón G, Rivas-Aceves S, Eds. The Future of Companies in the Face of a New Reality: Impact and Development in Latin America [Internet]. Philadelphia; Springer: 2021. pp. 131-47. Disponible en: https://doi.org/10.1007/978-981-16-2613-5_7
37. Al-Shamsi HO. The State of Cancer Care in the United Arab Emirates in 2022. Clinics and Practice [Internet]. 2022;12(6):955-85. Disponible en: https://doi.org/10.3390/clinpract12060101
38. Ryndach M, Sergeeva E, Churilina I, Chernenok M, Khismatullina E, Shostak M. Innovations in medical tourism. BIO Web of Conferences [Internet]. 2024;113: 06012. Disponible en: https://doi.org/10.1051/bioconf/202411306012
39. Wang K, Kong Haiyan B, Naipeng X, Honggen Q, Xuejie Li J. AI in health tourism: Developing a measurement scale. Asia Pacific Journal of Tourism Research [Internet]. 2022;27(9):954-66. Disponible en: https://doi.org/10.1080/10941665.2022.2142620
40. Spoladore D, Pessot E, Bischof M, Hartl A, Sacco M. Collaborative Design Approach for the Development of an Ontology-Based Decision Support System in Health Tourism. En: Camarinha-Matos LM, Boucher X, Afsarmanesh H, Eds. Smart and Sustainable Collaborative Networks 4.0 [Internet]. Philadelphia: Springer International Publishing; 2021. pp. 632-9. Disponible en: https://doi.org/10.1007/978-3-030-85969-5_59
41. Çolak O. The Role of Generative Pre-trained Transformers (GPT) in Recreational Tourism: An Interview with ChatGPT. Journal of Sport Sciences Research [Internet]. 2023; 8(3). Disponible en: https://doi.org/10.25307/jssr.1341967
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