Potential for Machine Learning in Burn Care

Abstract

Burn-related injuries are a leading cause of morbidity across the globe. Accurate assessment and treatment have been demonstrated to reduce the morbidity and mortality. This essay explores the forms of artificial intelligence to be implemented the field of burns management to optimize the care we deliver in the National Health Service (NHS) in the United Kingdom. Machine learning methods that predict or classify are explored. This includes linear and logistic regression, artificial neural networks, deep learning, and decision tree analysis. Utilizing machine learning in burns care holds potential from prevention, burns assessment, predicting mortality, and critical care monitoring to healing time. Establishing a regional or national Machine Learning group would be the first step toward the development of these essential technologies. The implementation of machine learning technologies will require buy-in from the NHS health boards, with significant implications with cost of investment, implementation, employment of machine learning teams, and provision of training to medical professionals.