Mohammad Javad Ghazanfari - Shahid Beheshti University of Medical Sciences, Tehran, Iran
Mustafa Esfandiari - Mazandaran University of Medical Sciences, Mazandaran, Iran
Akbar Zare Kaseb - Shahid Beheshti University of Medical Sciences, Tehran, Iran
Mohammad Hashem Gholampour - Mazandaran University of Medical Sciences, Mazandaran, Iran
Seyedah Mah Jabin Taheri Otaqhsara - Mazandaran University of Medical Sciences, Mazandaran, Iran
Mehsa Dadkhah Tehrani - Kashan University of Medical Sciences, Kashan, Iran

Introduction: Machine learning (ML) helps predict and make decisions about the diagnosis and treatment of diseases using data and previous experiences through statistical techniques and computer programs. One of the applications of ML is the diagnosis and management of burn wounds. However, ML for burn wound management is still questionable and challenging. The aim of this study was to the role of Machine learning for burned wound management from the nursing perspective.Materials and Methods: The protocol of the narrative review followed the PRISMA guideline. An extensive search was conducted in online databases including PubMed, ISI, Scopus, Google Scholar, Science direct with the keywords such as “Machine Learning”, “Transfer Learning”, “Artificial Intelligence”, “Burn”, “Wounds and Injuries”, “Wound Healing“, from the earliest records up to October ۲۰, ۲۰۲۲. Also, all original English articles related to the purpose of the present study were included in the study.Results: Various roles such as preparing ML algorithms for burn assessment and burn wound management, increasing sensitivity and accuracy in predicting burn-related complications such as acute kidney injury, classifying and identifying burns at different depths using the color and texture characteristics of laboratory images and Prediction of burn space and severity and spatial frequency domain imaging has been proposed for the diagnosis of burn wounds and decision making for skin grafting.Conclusion: Overall, it seems that ML can be considered as a new and promising technology for the management of burn wounds. However, evidence in this regard is limited. Therefore, it is suggested that future researchers design good studies to evaluate the role of ML in accurate assessment of patients and diagnostic and therapeutic measures for patients with burn wounds.

Machine Learning ،Artificial Intelligence ،Burn, Wounds and Injuries ،Wound Healing