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Published on: February 15, 2019
Artificial intelligence in wound care education: Scoping review
Rúben Encarnação1, José Alves2, Ana Marques3
1Centre for Interdisciplinary Research in Health, Faculty of Health Sciences and Nursing, Universidade Católica Portuguesa, 4169-005, Porto, Portugal; Cardiology Intensive Care Unit, São João Local Healthcare Unit, 4200-319, Porto, Portugal.
Background:
Artificial intelligence is transforming healthcare education, offering innovative teaching and skill development approaches. However, its implementation and effectiveness in wound care education remain unclear.
Objective:
To map and analyze the available evidence on the potential impact of artificial intelligence in wound care education, identify knowledge gaps, and provide recommendations for future research.
Design/Methods:
This scoping review followed the Joanna Briggs Institute guidelines for scoping reviews and the PRISMA-ScR guidelines. The search was first conducted in December 2023 and updated on 30 November 2024 across the following databases: CINAHL Ultimate, MEDLINE, Cochrane Library, Academic Search Complete, Scientific Electronic Library Online (Scielo), Scopus, and Web of Science. Grey literature was accessed through Scientific Open Access Scientific Repositories of Portugal (RCAAP), ProQuest Dissertations and Theses, OpenAIRE, and Open Dissertations. Additional searches were performed in Google Scholar and specific journals, including the International Wound Journal, Skin Research and Technology, Journal of Wound Care, and Wound Repair and Regeneration. Eligibility criteria encompassed any study design exploring the use of artificial intelligence in wound care education, published in English, Portuguese, or Spanish, with no restrictions on publication date.
Results:
This review revealed diverse artificial intelligence applications in wound care education, including adaptive e-learning platforms, virtual and augmented reality simulations, generative artificial intelligence for educational content, and diagnostic and treatment tools. These technologies offer personalized learning experiences, real-time feedback, and interactive engagement to enhance clinical skills. Despite their promise, most studies lacked empirical validation, highlighting significant gaps in integrating artificial intelligence into wound care education.
Conclusions:
This review highlights artificial intelligence's transformative potential to revolutionize wound care education by fostering interactive and evidence-based learning environments. This work highlights the need for collaboration among educators, policymakers, and researchers. Future research is needed to ensure effective, ethical, and equitable integration of artificial intelligence in wound care education.
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