Artificial Intelligence in Health Tourism Sustainability: A Systematic Review
Keywords:
Artificial intelligence, PRISMA methodology, sustainability, health tourism, medical tourismAbstract
Introduction: Artificial intelligence is emerging as a transformative tool to drive sustainability in health tourism, a rapidly growing sector, by optimizing resource management and personalizing experiences that respect the well-being of both visitors and the local environment.
Objective: To identify, analyze, and synthesize the role of artificial intelligence in the sustainability of health tourism through a systematic literature review.
Materials and Methods: A systematic review article based on the PRISMA methodology was conducted. Thirty-three studies from the Scopus and Web of Science databases were analyzed, with publications from 2020 to 2025. The variables studied were: artificial intelligence technologies, sustainability-oriented applications, destinations and activities associated with health tourism, economic and social implications, and opportunities and challenges of using artificial intelligence.
Results: Supervised learning, unsupervised learning, reinforcement learning, deep learning, neural networks, hybrid models, language models, and symbolic artificial intelligence are widely used technologies in health tourism. These technologies are applied in six functional areas: recommendation and decision support systems, demand forecasting and strategic planning, service segmentation and personalization, operational process automation, multilingual communication and accessibility, and remote clinical diagnosis and monitoring.
Conclusions: Artificial intelligence actively contributes to the sustainability of health tourism by optimizing resources, improving the patient experience, and strengthening the competitiveness of destinations.
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