Artificial intelligence Applications in Pre-Hospital Care

Artificial intelligence (AI) is transforming healthcare across various domains, including pre-hospital emergency medical services (EMS). The integration of AI technologies such as machine learning, predictive analytics, and voice recognition tools enables EMS teams to provide prompt and accurate care, often before patients arrive at the hospital. This article examines the incorporation of AI in pre-hospital care, with a particular focus on the use of portable ultrasound devices, machine learning algorithms, and voice-activated technologies. These advancements are critical for detecting and managing conditions such as acute coronary syndrome, spinal cord injuries, and traumatic brain injuries, which are commonly encountered in emergency situations. We evaluate the benefits of these technologies, including improved diagnostic accuracy, reduced response times, and enhanced decision-making capabilities, through a review of current literature. The challenges associated with integrating AI in pre-hospital settings are also discussed, such as data privacy concerns, the need for training, and integration with existing systems. Recommendations for future research and the application of these technologies in emergency contexts are provided, focusing on overcoming barriers to adoption and facilitating seamless integration into EMS protocols.