We are proud to announce that we played a key role in a new landmark study highlighting the potential of artificial intelligence (AI) to support lifesaving decisions in trauma care.
The study, published in the Emergency Medicine Journal, evaluated a machine learning system designed to predict trauma-induced coagulopathy. This is a life-threatening condition which can make it difficult for blood to clot following major injury. Identifying it early is crucial, but challenging, in pre-hospital emergency medicine.
Conducted in collaboration with Queen Mary University of London, London’s Air Ambulance, Defence Medical Services and other leading trauma and AI experts, the study assessed the performance of machine learning against expert clinicians in real pre-hospital cases, including patients seen by KSS. Machine learning is a subset of AI that enables machines to learn from data and improve their performance without being explicitly programmed.
The research shows that a machine learning system could provide clinicians with a powerful tool to help identify patients who might benefit from early blood transfusion and the advanced interventions which KSS can provide.
Professor Richard Lyon MBE, our Executive Director of Research & Innovation and Deputy Medical Director and co-author of the study, said: “This research represents a major step forward in harnessing AI to support critical decision-making in the earliest moments of trauma care. At KSS, we are committed to research and innovation that saves lives, and this study shows how technology could empower clinicians to make faster, more accurate, decisions in the future.”
The study lays the groundwork for future larger trials and the integration of AI tools into routine trauma care. We are at the forefront of this innovation, committed to improving outcomes for critically injured patients across the South East of England and beyond.
