Identificador persistente para citar o vincular este elemento: https://accedacris.ulpgc.es/jspui/handle/10553/161635
Título: Applications of 3D printing and artificial intelligence in healthcare management: a narrative review
Autores/as: Domínguez Trujillo, Conrado Jesús 
Monopoli Forleo, Donato
Dávila Quintana, Carmen Delia 
Mora Delgado, Juan
Clasificación UNESCO: 531207 Sanidad
Palabras clave: Artificial Intelligence
Biomedical Engineering
Bioprinting
Machine Learning
Patient-Specific Modeling, et al.
Fecha de publicación: 2026
Publicación seriada: Bioengineered 
Resumen: The integration of 3D printing and artificial intelligence is transforming healthcare management by driving innovations in personalized care, supply chain operations, and clinical workflows. This review offers a comprehensive overview and in-depth analysis of recent (2018–2025) applications where AI technologies enhance 3D printing within healthcare. We explore how AI-powered design and optimization facilitate the creation of patient-specific medical devices, implants, and even bioprinted tissues, while intelligent process control increases both quality and efficiency. Additionally, we examine regulatory and ethical considerations, including the evolution of frameworks for AI-enabled devices, as well as challenges in data governance, validation, and equitable access. The review takes a global perspective, presenting real-world case studies that showcase both successful implementations and ongoing challenges. We also discuss various perspectives and controversies, such as the balance between innovation and safety in autonomous AI design, and highlight areas where further research is needed. In contrast to previous narrative reviews that focus solely on clinical applications or technical aspects, this review uniquely evaluates the combined impact of AI and 3D printing on healthcare management—including cost-effectiveness, governance, decision-making processes, and point-of-care manufacturing. This work is particularly valuable for hospital administrators, clinical operations leaders, health policymakers, and biomedical innovation teams seeking to understand the broader implications of AI-enhanced 3D printing in healthcare management. Nevertheless, despite promising advancements, the field is constrained by heterogeneous evidence, a lack of standardized evaluation metrics, and insufficient long-term outcome data, which together limit the ability to fully assess the sustained impact of AI-integrated 3D printing in healthcare environments.
URI: https://accedacris.ulpgc.es/jspui/handle/10553/161635
DOI: 10.3390/bioengineering13020196
Fuente: Bioengineering[EISSN 2306-5354],v. 13 (2), (Febrero 2026)
Colección:Artículos
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