Revolutionizing Emergency Care with AI: Predictive Models for Critical Interventions

Abstract

AI is transforming emergency care by enabling rapid decision-making and resource allocation during critical situations. This paper examines the use of predictive analytics to identify high-risk patients, optimize triage processes, and forecast emergency department overcrowding. It presents case studies on AI-driven tools that predict cardiac arrests, strokes, and sepsis in real-time. The study also discusses challenges in integrating AI into fast-paced environments and ensuring the reliability of predictions under diverse conditions.