ABSTRACT Artificial intelligence (AI) is expanding its footprints across all our activities. The main tools of AI include machine learning, artificial neural networks, natural language processing, and computer vision. It has been used across various medical specialties, and there are numerous studies that have investigated and validated various tools of AI in clinical practice. Plastic surgery and its subspecialties like burns have always been in the forefront of surgical innovations. We discuss the various articles that have used AI tools for burn management. AI tools have been successfully used to calculate the TBSA and depth of burns from burn photographs. AI algorithms have been used in clinical decision-making in burn critical care like early recognition of sepsis and acute kidney injury and also prediction of need for ventilation. Artificial neural networks have looked at optimum serum concentrations of antibiotics in severe burn patients. There are tools incorporating AI to surgical robotics and surgical decision-making. AI has been extensively used in the prediction of burn mortality and length of stay calculations. The unique nature of injury in burn patients and the developments of AI till now in this field leave burn management in an exceptionally good position to harness the next phases of innovations in AI.
Goswami et al. (2025) studied this question.