Current and Emerging Applications of Artificial Intelligence in the Clinical Management of Burn Patients: A Scoping Review.

EXECUTIVE SUMMARY Introduction: Artificial Intelligence (A I) is considered an emerging tool within computer sciences, using logic processes, algorithms, machine learning, and deep learning to simulate human mind functions such as intelligence, reasoning, and information processing [1].. This tool has had a significant impact in healthcare, notably in the creation and use of applications for diagnostic support and medical/surgical decision-making in various clinical settings. These applications have enabled healthcare professionals to improve diagnostic accuracy, prevent and anticipate possible complications, and personalize and adjust treatment according to each patient's needs [1].. In plastic and reconstructive surgery, there is growing interest in using these tools for the care and management of burn patients, as well as for optimizing rehabilitation processes and preventing chronic sequelae[2]. This scoping review aims to explore the current and emerging applications of AI in the comprehensive management of burn patients, identifying benefits, limitations, and possible future recommendations. Methodology: A scoping review will be conducted of observational studies, original and scientific articles, meta-analyses, systematic or scoping reviews, and gray literature published between 2010 and 2025, in English or Spanish. A comprehensive search will be performed in electronic databases such as PubMed, Scopus, Web of Science, SciELO, and LILACS, using MeSH descriptors related to AI and its application in plastic surgery and burn patient management. As a complementary strategy, the snowball technique will be applied to the bibliographic references of selected articles to identify additional relevant studies not retrieved in the initial search. Expected Results: The results are expected to provide a comprehensive view of current AI uses in plastic and reconstructive surgery focused on burn patient management, identifying especially successful cases, possible obstacles encountered, and recommendations for the potential application of this tool in the field. The findings will be aimed at researchers, healthcare professionals, or anyone interested in AI applications for burn patient care.