Artificial intelligence-assisted smart first aid decision support system for early injury assessment, emergency response, andnursing management in community and hospital settings

Abstract

Artificial intelligence (AI) is transforming emergency healthcare by enhancing the speed, accuracy, and consistency of first aid decision-making in both community and hospital settings. Timely first aid plays a critical role in reducing mortality, preventing complications, and improving recovery following injuries and acute medical emergencies; however, delayed recognition of life-threatening conditions, variations in clinical judgement, and limited access to trained responders continue to compromise patient outcomes. AI-assisted smart first aid decision support systems integrate machine learning, deep learning, computer vision, natural language processing, wearable sensors, cloud computing, and Internet of Medical Things (IoMT) technologies to analyse patient data in real time and provide evidence-based recommendations for early injury assessment and emergency management. These intelligent systems support the identification of trauma, burns, fractures, cardiac events, stroke, respiratory emergencies, and other critical conditions while facilitating rapid communication with emergency medical services and healthcare professionals. For nurses, AI enhances clinical assessment, triage, patient monitoring, documentation, medication safety, and multidisciplinary collaboration, enabling more efficient and standardised care without replacing professional judgement or compassionate practice. The application of AI extends beyond hospitals to community healthcare, ambulance services, schools, workplaces, disaster response, and home-based care, thereby improving access to timely emergency guidance and strengthening healthcare preparedness. Although challenges related to data privacy, cybersecurity, algorithmic bias, ethical governance, infrastructure, and professional training remain, continued technological advancements and responsible implementation are expected to enhance the effectiveness and reliability of AI-assisted emergency care. The integration of intelligent decision support with skilled nursing practice has the potential to improve patient safety, optimise emergency response, reduce preventable complications, and contribute to more resilient, patient-centred healthcare systems.